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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 17 Dec 2012 16:33:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/17/t1355780047wujyp6vpvkqdzeb.htm/, Retrieved Fri, 26 Apr 2024 06:41:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201221, Retrieved Fri, 26 Apr 2024 06:41:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2012-12-17 21:33:36] [311e8979fc66fc3b169c8163f1497ef3] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
110.92	89.06	3566.59	38.58
111.19	88.96	3557.28	38.48
111.19	88.95	3568.88	38.56
110.42	87.66	3515.19	38.25
109.69	86.62	3502.13	37.97
110.03	87.03	3500.94	38.42
110.77	87.83	3528.8	38.6
111.34	88.14	3498.22	38.3
111.34	88.28	3477.36	38.22
110.41	87.06	3462.06	38.22
111.05	87.69	3439.58	38.22
110.44	87.34	3341.52	36.98
111.56	88.94	3382.4	37.43
109.48	87.59	3400.02	37.52
109.18	87.12	3430.6	37.98
107.69	85.78	3411.65	37.83
108.7	86.7	3423.57	38
107.19	85.69	3407.68	37.7
107.84	85.92	3409.59	37.88
108.33	86.59	3478.66	39.02
109.4	86.06	3448.5	38.84
107.08	85.03	3492.46	39.44
106.75	84.69	3475.4	39.12
111.02	88.25	3429.27	38.82
107.81	85.79	3459.44	38.99
105.44	84.78	3408.89	38.39
105.75	84.83	3435.09	38.71
108.15	86.89	3411.53	38.43
108.47	86.12	3426.49	38.67
108.96	85.71	3406.5	38.45
109.29	85.28	3483.25	39.34
109.23	85.95	3504.56	39.6
109.61	86.17	3535.18	39.84
108.56	86.19	3527.5	40
107.77	85.77	3500.94	39.55
108.25	86.69	3420.28	38.5
109.72	89.23	3389.08	38.13
109.57	89.91	3413.72	38.75
110.14	90.51	3365.87	38.2
112.47	92.48	3382.78	38.39
113.17	92.42	3406.53	38.29
113.7	92.92	3457.04	38.73
114.47	92.19	3401.2	38.33
113.05	91.53	3406.02	38.73
114.56	91.62	3414.23	39.06
115.72	92.47	3434.98	39.28
114.51	91.27	3354.82	38.6
114.42	91.88	3439.32	39.68
112.06	89.99	3414.84	39.61
111.59	89.68	3513.81	40.74
111.9	89.92	3497.22	40.55
112.25	91.48	3530.72	40.8
108.07	88.34	3509.92	40.81
111.3	91.66	3531.82	41.47
112.23	92.43	3512.69	41
111.88	91.5	3553.69	41.42
112.14	92.03	3581.58	41.84
112.47	92.22	3502.09	40.89
110.11	90.31	3543.79	41.05
109.96	90.86	3537.3	41.2
109.86	92.1	3506.05	40.45
111.41	92.9	3519.05	40.55
111.56	93.06	3509.88	40.5
110.56	92.82	3405.79	39.23
108.36	92.19	3399.04	39.42
111.67	95.78	3453.71	40.05
113.6	97.3	3413.07	39.7
116.85	99.3	3379.11	39.17
116.7	98.99	3413.89	39.42
115.64	98.14	3431.55	39.24
115.27	96.96	3462.83	39.6
114.41	96.88	3433.21	39.38
114.26	96.25	3432.56	39.38
113.91	96.31	3461.65	39.8
114.54	96.34	3513.28	40.45
112.6	94.83	3480.58	40.45
113.78	95.78	3488.38	40.38
114.17	95.36	3480.49	40.25
115.78	96.86	3449.2	40.03
114.59	96.19	3450.27	40
114.88	96.44	3426.41	39.76
112.79	94.57	3435.62	39.96
112.73	95.15	3456.71	40
112.38	96.17	3438.26	39.9
112.59	95.67	3453.28	39.76
114.21	96.76	3401.56	38.9
113.47	96.09	3374.19	38.92
114.44	95.92	3232.46	37.34
115.03	97.36	3321.56	37.99
114.86	96.84	3291.66	37.6
113.61	96.17	3320.71	37.45
114.08	96.19	3280.19	37.35
113.73	96.17	3207.12	36.12
114.4	95.3	3081.74	34.83
114.48	94.36	3074.68	34.83
112.08	93.14	3101.53	35.39
111.58	92.58	3193.89	36.05
111.44	93.23	3263.64	36.66
113.38	93.35	3235.4	36.54
113.3	93.53	3176.97	35.87
112.03	93.32	3179.9	36.01
111.69	93.29	3180.81	36.03
109.56	91.88	3135.18	35.63
108.5	91.25	3157.25	36.04
109.01	91.36	3175.41	35.96
105.87	87.44	3156.8	35.94
105.81	88.73	3168.79	36.06
104.62	87.75	3229.36	36.52
106.05	89.61	3267.75	36.91
106.44	90.02	3271.2	37.05
106.55	90.13	3240.2	35.98
105.33	89.16	3196.65	35.5
104.61	88.77	3051.68	34.04
103.05	88.21	3063.12	34.2
103.27	87.98	3012.71	33.63
106.32	91.25	3021.64	33.84
106.71	91.59	3090.9	34.41
107.55	92.44	3114.22	34.84
105.54	90.19	3126.52	35.2
103.58	89.34	3117.92	35.3
103.13	88.52	3066.19	34.8
101.66	87.5	3087.62	35.43
102.69	87.07	3032.45	34.88
100.66	85.66	3030.04	34.81
100.68	86	3046.91	34.83
97.92	84.33	3042.76	34.7
100.28	85.17	3051.69	34.59
98.3	84.36	3071.16	34.77
97.83	84.06	3058.44	34.8
100.03	86.92	2986.1	34.32
99.72	86.88	2954.49	33.96
100.65	87.68	2950.47	34
97.35	83.35	3017.01	34.77
97.38	84.56	3015.58	34.53
97.62	85.02	3084.7	35.2
92	78.39	3042.97	35.06
93.78	80.41	3047.94	35.18
93.19	79.43	3038.25	35
91.36	79.3	3003.27	34.49
91.34	80.05	3084.09	35.15
91.39	80.11	3027.15	34.59
89.23	78.43	3008	34.65
92.66	80.75	3011.99	34.59
95.76	84.31	3048.67	34.92
95.73	83.45	3039.27	34.37
98.66	85.11	3057.99	34.47
97.53	84.05	3129.77	35.13
97.81	84.3	3130.17	35.15
96.56	82.59	3118.65	34.48
97.16	83.08	3124.8	34.91
96.25	81.5	3214.22	35.95
101.86	86.44	3161.97	35.52
99.95	84.46	3223.36	36.16
99.17	83.92	3226.33	36.15
100.92	85.39	3212.8	36.07
98.65	84.4	3266.27	36.5
98.97	84.42	3229.32	36.51
97.83	82.46	3233.46	36.23
98.75	83.28	3169.32	35.91
101.63	86.57	3098.37	35.56
103.15	87.7	3188.58	36.45
106.88	90.72	3174.02	36.34
107.28	91.06	3240.29	37.32
106.98	91.32	3292.51	37.47
106.75	90.75	3205.28	36.98
106.84	90.83	3189.09	36.42
106.16	90.28	3269.79	37.04
108.22	91.52	3237.69	37.15
109.28	93.22	3217.6	37.13
106.92	91.56	3319.81	38.21
107.14	91.32	3313.47	37.91
106.86	92.61	3406.78	38.4
109.34	92.94	3462.91	39.12
111.03	93.32	3423.81	38.05
110.33	94.28	3381.12	37.83
111.43	95.5	3430.15	38.02
112.06	95.65	3469.59	38.43
112.24	96.19	3501.98	40.94
112.7	96.43	3476.18	40.75
113.23	97.11	3472.46	41.06
113.44	98.08	3530	41.69
111.25	96.27	3530.83	41.73
113.47	98.55	3577.88	42.34
115.98	102.56	3594.83	42.54
118.33	105.28	3580.21	42.5
119.72	105.84	3564.51	42.78
119.42	104.84	3550.16	42.65
119.53	104.8	3490.06	42
119.64	104.78	3487.48	42.3
119.17	104.02	3478.36	42.02
118.45	103.75	3392.33	41.52
118.71	103.1	3362	41.77
118.81	103.86	3487.54	42.43
118.85	104.08	3501.17	42.43
118.12	103	3499.73	42.48
118.14	103.22	3452.45	42.01
118.71	104.77	3453.99	41.99
118.44	103.61	3441.45	42.01
120.48	102.83	3467.03	42.05
121.39	102.86	3447.31	41.84
121.52	103.83	3447.37	41.79
119.79	102.62	3465.24	41.82
119.39	100.95	3472.54	41.87
121.97	102.34	3439.62	41.66
121.72	102.19	3393.25	41.19
123.3	103.25	3390.35	40.99
122.69	102.08	3375.64	41.15
124.98	103.98	3384.55	40.95
125.37	104.92	3373.14	40.67
123.42	103.44	3424.71	41.1
122.92	102.97	3410	40.88
122.56	103.3	3411.54	40.93
124.31	105.56	3405.27	40.89
125.2	106.89	3427.92	40.97
125.73	107.05	3376.66	40.87
124.94	106.74	3367.46	40.56
125.11	106.8	3298.55	40.47
123.32	105.66	3265.64	40.01
124.07	106.93	3318.76	40.23
124.05	106.39	3360.7	40.45
125.28	108.19	3312.48	40.3
125.95	107.86	3322.65	40.38
126.06	107.22	3338.42	39.95
122.73	105.5	3321.5	39.74
124.47	105.66	3328.94	40.37
125.61	106.85	3264.93	40.05
125.05	106.62	3269.99	40.14
125.05	107.13	3225	39.42
125.94	107.42	3196.49	38.97
125.57	106.89	3199.98	39.06
124.25	106.14	3204.83	39.86
122.19	104.94	3210.79	40.49
124.2	107.17	3144.64	39.99
123.59	106.85	3137.36	39.94
123.63	106.58	3144.91	39.97
125.96	108.94	3193.65	40.21
122.95	107.03	3245.4	40.39
121.77	106.61	3222.3	39.95
123.38	107.97	3159.81	39.46
125.28	109.59	3127.56	39.07
125.31	109.7	3071.08	38.64
124.12	108.58	3103.11	38.96
122.64	105.96	3102.09	38.57
121.5	106	3069.3	37.84
120.03	105.03	3030.47	37.36
120.73	105.14	3055.39	37.08
119.76	104.28	2974.2	36.45
120.06	102.58	2972.3	37.02
119.04	102.2	2998.73	37.68
117.49	101.25	2976.17	37.67
117.23	100.92	3078.72	38.55
117.41	99.64	3089.59	38.16
117.66	99.02	3172.35	38.96
118.66	99.72	3095.49	38.05
117.83	98.97	3175.98	38.77
116.05	98.72	3179.63	38.76
116.46	97.19	3201.28	38.86
114.94	97.69	3164.95	38.49
114.66	97.83	3129.95	38.29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 16 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Total[t] = -9.54860616351923 + 0.0276389178077004Brent[t] + 0.0692672424005859WTI[t] + 0.0112358608496097Cac40[t] + 0.00917107516437388t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Total[t] =  -9.54860616351923 +  0.0276389178077004Brent[t] +  0.0692672424005859WTI[t] +  0.0112358608496097Cac40[t] +  0.00917107516437388t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Total[t] =  -9.54860616351923 +  0.0276389178077004Brent[t] +  0.0692672424005859WTI[t] +  0.0112358608496097Cac40[t] +  0.00917107516437388t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
Total[t] = -9.54860616351923 + 0.0276389178077004Brent[t] + 0.0692672424005859WTI[t] + 0.0112358608496097Cac40[t] + 0.00917107516437388t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-9.548606163519230.891673-10.708600
Brent0.02763891780770040.0197871.39680.1636960.081848
WTI0.06926724240058590.0246722.80750.005380.00269
Cac400.01123586084960970.00032834.212900
t0.009171075164373880.001157.976500

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & -9.54860616351923 & 0.891673 & -10.7086 & 0 & 0 \tabularnewline
Brent & 0.0276389178077004 & 0.019787 & 1.3968 & 0.163696 & 0.081848 \tabularnewline
WTI & 0.0692672424005859 & 0.024672 & 2.8075 & 0.00538 & 0.00269 \tabularnewline
Cac40 & 0.0112358608496097 & 0.000328 & 34.2129 & 0 & 0 \tabularnewline
t & 0.00917107516437388 & 0.00115 & 7.9765 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-9.54860616351923[/C][C]0.891673[/C][C]-10.7086[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Brent[/C][C]0.0276389178077004[/C][C]0.019787[/C][C]1.3968[/C][C]0.163696[/C][C]0.081848[/C][/ROW]
[ROW][C]WTI[/C][C]0.0692672424005859[/C][C]0.024672[/C][C]2.8075[/C][C]0.00538[/C][C]0.00269[/C][/ROW]
[ROW][C]Cac40[/C][C]0.0112358608496097[/C][C]0.000328[/C][C]34.2129[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]t[/C][C]0.00917107516437388[/C][C]0.00115[/C][C]7.9765[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-9.548606163519230.891673-10.708600
Brent0.02763891780770040.0197871.39680.1636960.081848
WTI0.06926724240058590.0246722.80750.005380.00269
Cac400.01123586084960970.00032834.212900
t0.009171075164373880.001157.976500






Multiple Linear Regression - Regression Statistics
Multiple R0.960667624226281
R-squared0.922882284236566
Adjusted R-squared0.921667832019819
F-TEST (value)759.916505161962
F-TEST (DF numerator)4
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.651267077413488
Sum Squared Residuals107.733796755167

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.960667624226281 \tabularnewline
R-squared & 0.922882284236566 \tabularnewline
Adjusted R-squared & 0.921667832019819 \tabularnewline
F-TEST (value) & 759.916505161962 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.651267077413488 \tabularnewline
Sum Squared Residuals & 107.733796755167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.960667624226281[/C][/ROW]
[ROW][C]R-squared[/C][C]0.922882284236566[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.921667832019819[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]759.916505161962[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.651267077413488[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]107.733796755167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.960667624226281
R-squared0.922882284236566
Adjusted R-squared0.921667832019819
F-TEST (value)759.916505161962
F-TEST (DF numerator)4
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.651267077413488
Sum Squared Residuals107.733796755167






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
138.5839.7689232306809-1.1889232306809
238.4839.6740242249035-1.19402422490347
338.5639.8128386134993-1.2528386134993
438.2539.1081196102394-0.858119610239446
537.9738.8783360006117-0.90833600061169
638.4238.9119332028039-0.491933202803883
738.639.3100019543366-0.710001954336552
838.339.0128074330144-0.712807433014432
938.2238.797295864792-0.577295864792031
1038.2238.5243480396675-0.304348039667498
1138.2238.3422642330419-0.122264233041943
1236.9837.2085435185907-0.22854351859069
1337.4337.8188197610727-0.388819761072668
1437.5237.8749669781264-0.354966978126353
1537.9838.1868833988012-0.206883398801212
1637.8337.8491348185152-0.0191348185152236
173838.0838785250013-0.0838785250012611
1837.737.8028170905511-0.10281709055111
1937.8837.86734542226540.0126545777346172
2039.0238.71252952844650.307470471553539
2138.8438.37568904396850.464310956031463
2239.4438.74332101309530.696678986904709
2339.1238.52813659687260.591863403127417
2438.8238.38360697302940.436393026970576
2538.9938.47264562755840.517354372441637
2638.3937.77837978674610.611620213253877
2738.7138.09396184281070.61603815718931
2838.4338.04743995844190.38256004155805
2938.6738.18020818896650.489791811033509
3038.4537.94991790608870.5000820939113
3139.3438.80077723010490.539222769895091
3239.639.09413521731440.505864782685603
3339.8439.47308993378890.366910066211128
344039.36833407877820.631665921221825
3539.5539.02815370290060.521846297099411
3638.538.20803278549170.291967214508322
3738.1338.0832130070230.0467869929769685
3838.7538.4121915806830.337808419316968
3938.237.94104124278430.258958757215679
4038.3938.34106587093670.0489341290633026
4138.2938.6322798492007-0.342279849200658
4238.7339.2582565035172-0.528256503517192
4338.3338.6107339885989-0.280733988598858
4438.7338.5890982697870.140901730212967
4539.0638.73848458023240.321515419767622
4639.2839.07173806872360.208261931276415
4738.638.06367875675520.536321243244774
4839.6839.06204558897330.617954411026714
4939.6138.60001985637591.00998014362407
5040.7439.68674094331241.05325905668763
5140.5539.53470128967831.01529871032175
5240.840.03800422268220.761995777317837
5340.8139.48043957460061.32956042539938
5441.4740.05491695166031.41508304833973
554139.92818597898121.07181402101878
5641.4240.32393519231441.09606480768565
5741.8440.69037218367671.14962781632335
5840.8939.82868629883821.06131370116179
5941.0540.108864492420.941135507579984
6041.240.07906597631961.12093402368041
6140.4539.82024388872960.629756111270386
6240.5540.07373527146130.476264728538675
6340.539.995102099090.504897900909978
6439.2338.79046936243470.439530637565318
6539.4238.61935439497490.800645605025125
6640.0539.5829442009490.46705579905099
6739.739.2941192110030.405880788997007
6839.1739.15008141939080.0199185806091803
6939.4239.5244170520893-0.104417052089279
7039.2439.6438390209411-0.403839020941104
7139.639.9125060778597-0.312506077859726
7239.3839.559560105952-0.179560105951991
7339.3839.5136436711806-0.133643671180594
7439.839.8441483517715-0.044148351771462
7540.4540.4529174580921-0.00291745809204928
7640.4539.93646284690240.513537153097642
7740.3840.13169143998730.248308560012666
7840.2540.0338985091850.216101490814956
7940.0339.83989901963640.190100980363595
804039.78179310131030.218206898689692
8139.7639.54820863336740.211791366632625
8239.9639.47356690544950.486433094550538
834039.7582189514560.241781048544014
8439.939.6210673599610.278932640039034
8539.7639.7701716166258-0.0101716166258026
8638.939.3185003097135-0.418500309713472
8738.9238.9532840218379-0.0332840218379352
8837.3437.3850308578525-0.0450308578524933
8937.9938.5113689252805-0.521368925280479
9037.638.1438701789659-0.543870178965909
9137.4538.3984853121434-0.948485312143427
9237.3537.9667549418992-0.616754941899248
9336.1237.1438626987019-1.02386269870194
9434.8335.7025371145849-0.872537114584893
9534.8335.5694829177191-0.739482917719087
9635.3935.7294974182283-0.339497418228288
9736.0536.7238034868144-0.673803486814436
9836.6637.5578301153064-0.897830115306391
9936.5437.3116320497128-0.771632049712795
10035.8736.674548765642-0.804548765641962
10136.0136.6669933665758-0.656993366575791
10236.0336.6749138257867-0.64491382578667
10335.6336.0148548636681-0.384854863668123
10436.0436.1990657721949-0.159065772194856
10535.9636.4339953251341-0.473995325134131
10635.9435.87575323776080.0642467622392011
10736.0636.1073386921403-0.0473386921402804
10836.5236.6962936492218-0.176293649221777
10936.9137.3051701457328-0.395170145732774
11037.0537.3922836881575-0.342283688157542
11135.9837.0638027546069-1.08380275460693
11235.536.4827433849168-0.982743384916835
11334.0434.8161374673555-0.776137467355515
11434.234.8719404231151-0.67194042311508
11533.6334.3048608490162-0.67486084901619
11633.8434.725170743531-0.885170743530978
11734.4135.5468675815005-1.13686758150053
11834.8435.9001527786768-1.06015277867676
11935.235.8361194220965-0.636119422096541
12035.335.6356126590107-0.335612659010687
12134.834.9943160006428-0.194316000642804
12235.4335.13298977738840.297010222611607
12334.8834.52096158058950.359038419410526
12434.8134.34928041617180.460719583828167
12534.8334.57210410464150.257895895358521
12634.734.34268664932170.357313350678259
12734.5934.57560629151580.0143937084842081
12834.7734.69270805381830.0772919461816568
12934.834.52518851488590.274811485114105
13034.3233.98046734863210.339532651367886
13133.9633.62313410812390.336865891876087
1323433.66825501015450.331744989845513
13334.7734.03392467789190.736075322108057
13434.5334.11167100288030.418328997119685
13535.234.93596105174780.264038948252174
13635.0633.86168711846281.19831288153717
13735.1834.11581752539671.06418247460334
1383533.93192424986921.06807575013081
13934.4933.48848095141411.00151904858595
14035.1534.45713195388820.692868046111829
14134.5933.83207109271020.757928907289817
14234.6533.45000640290691.19999359709308
14334.5933.7595100533110.830489946689001
14434.9234.5130845325890.406915467410981
14534.3734.35623951976830.0137604802316702
14634.4734.7717115615989-0.301711561598928
14735.1335.482737474481-0.352737474480963
14835.1535.5214586015715-0.371458601571488
14934.4835.2481969279837-0.768196927983733
15034.9135.3769928468341-0.466992846834115
15135.9536.2562809409727-0.306280940972645
15235.5236.175612793105-0.655612793105005
15336.1636.6846138928611-0.524613892861061
15436.1536.6681928079624-0.51819280796245
15536.0736.6755336383239-0.605533638323942
15636.537.1541712797169-0.654171279716886
15736.5136.7584070950347-0.24840709503466
15836.2336.6468224727105-0.416822472710491
15935.9136.0175523761325-0.107552376132465
16035.5635.53702843480110.0229715651988746
16136.4536.6800696561892-0.230069656189159
16236.3436.8379268328557-0.497926832855706
16337.3237.626304836063-0.306304836062998
16437.4738.2319303724758-0.761930372475837
16536.9837.2151580264646-0.235158026464654
16636.4237.0504493964686-0.630449396468581
16737.0437.9094629947669-0.8694629947669
16837.1537.7007904879194-0.550790487919393
16937.1337.6312846835723-0.501284683572261
17038.2138.6086616277641-0.3986616277641
17137.9138.5360537688835-0.626053768883503
17238.439.6752588656356-1.27525886563556
17339.1240.4065015164438-1.28650151644382
17438.0540.0493817555957-1.99938175559569
17537.8339.6260432413294-1.79604324132939
17638.0240.3010174192673-2.28101741926731
17738.4340.7811334509192-2.35113345091924
17840.9441.1966133751042-0.256613375104173
17940.7540.9452372807163-0.195237280716296
18041.0640.97436130479060.085638695209399
18141.6941.7030372111097-0.0130372111097065
18241.7341.53563111203530.194368887964668
18342.3442.29273715038030.0472628496197313
18442.5442.8394913926692-0.299491392669207
18542.542.93775253839-0.437752538389977
18642.7842.8477283497125-0.0677283497125115
18742.6542.61810590394210.0318940960579113
1884241.95227133330770.0477286666922579
18942.341.9341088235910.365891176409037
19042.0241.77517545221280.244824547787174
19141.5240.77912324221560.740876757784428
19241.7740.40967306888091.36032693111909
19342.4341.88480111111050.545198888889499
19442.4342.06346131969550.366538680304508
19542.4841.96146772344420.518532276555823
19642.0141.45519886932330.554801130676717
19741.9941.60479157906740.385208420932651
19842.0141.38525245018490.624747549815137
19942.0541.68419178913750.36580821086249
20041.8441.49902112082460.340978879175403
20141.7941.57964863208350.21035136791648
20241.8241.65797584951840.162024150481613
20341.8741.62243684695290.247563153047142
20441.6641.42931325782880.230686742171239
20541.1940.90017764958470.28982235041528
20640.9940.993857495366-0.00385749536600836
20741.1540.73984664396120.410153356038757
20840.9541.0440301216364-0.0940301216363869
20940.6741.0008904103083-0.330890410308265
21041.141.4330834210091-0.333083421009131
21140.8841.2305999202436-0.350599920243619
21240.9341.2699824006978-0.339982400697815
21340.8941.4136167023239-0.523616702323936
21440.9741.7940040949736-0.824004094973604
21540.8741.2529563282092-0.382956328209159
21640.5641.1154498933449-0.555449893344855
21740.4740.3592124479340.110787552066026
21840.0139.87017302332520.139826976674762
21940.2340.5848916130254-0.354891613025404
22040.4541.0273376029699-0.577337602969928
22140.340.6533923731907-0.353392373190656
22240.3840.7724920381345-0.392492038134522
22339.9540.9175618847197-0.967561884719713
22439.7440.52544494108-0.78544494108004
22540.3740.677385296735-0.307385296735008
22640.0540.0812853036733-0.0312853036733374
22740.1440.11590057501230.0240994249877138
22839.4239.654896564177-0.234896564177019
22938.9739.388419383664-0.418419383664045
23039.0639.3898655751324-0.329865575132395
23139.8639.36509677211080.494903227889226
23240.4939.30117671637431.18882328362575
23339.9938.77711577168371.21288422831627
23439.9438.66546452243211.27453547756793
23539.9738.74186974827511.22813025172486
23640.2139.52654605180680.683453948193185
23740.3939.90167935035220.488320649647805
23839.9539.58959587506930.360404124930749
23939.4639.03534011307670.424659886923292
24039.0738.84688155236470.22311844763525
24138.6438.22989977094150.410100229058537
24238.9638.4884858454390.471514154560983
24338.5738.26381056909190.306189430908143
24437.8437.8758200903928-0.0358200903927714
24537.3637.34088425446090.0191157455390873
24637.0837.657019621127-0.577019621127017
24736.4536.6675715751736-0.217571575173601
24837.0236.5459318779850.474068122014966
24937.6836.79755350712850.882446492871483
25037.6736.44459935864321.2254006413568
25138.5537.57596365531290.974036344687142
25238.1637.62358147284510.536418527154871
25338.9638.52659643108680.433403568913243
25438.0537.74830522883820.301694771161758
25538.7738.58696001020690.183039989793133
25638.7638.57062789317450.189372106825531
25738.8638.72840843116110.131591568838847
25838.4938.32200314779180.167996852208212
25938.2937.93987761016980.350122389830249

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38.58 & 39.7689232306809 & -1.1889232306809 \tabularnewline
2 & 38.48 & 39.6740242249035 & -1.19402422490347 \tabularnewline
3 & 38.56 & 39.8128386134993 & -1.2528386134993 \tabularnewline
4 & 38.25 & 39.1081196102394 & -0.858119610239446 \tabularnewline
5 & 37.97 & 38.8783360006117 & -0.90833600061169 \tabularnewline
6 & 38.42 & 38.9119332028039 & -0.491933202803883 \tabularnewline
7 & 38.6 & 39.3100019543366 & -0.710001954336552 \tabularnewline
8 & 38.3 & 39.0128074330144 & -0.712807433014432 \tabularnewline
9 & 38.22 & 38.797295864792 & -0.577295864792031 \tabularnewline
10 & 38.22 & 38.5243480396675 & -0.304348039667498 \tabularnewline
11 & 38.22 & 38.3422642330419 & -0.122264233041943 \tabularnewline
12 & 36.98 & 37.2085435185907 & -0.22854351859069 \tabularnewline
13 & 37.43 & 37.8188197610727 & -0.388819761072668 \tabularnewline
14 & 37.52 & 37.8749669781264 & -0.354966978126353 \tabularnewline
15 & 37.98 & 38.1868833988012 & -0.206883398801212 \tabularnewline
16 & 37.83 & 37.8491348185152 & -0.0191348185152236 \tabularnewline
17 & 38 & 38.0838785250013 & -0.0838785250012611 \tabularnewline
18 & 37.7 & 37.8028170905511 & -0.10281709055111 \tabularnewline
19 & 37.88 & 37.8673454222654 & 0.0126545777346172 \tabularnewline
20 & 39.02 & 38.7125295284465 & 0.307470471553539 \tabularnewline
21 & 38.84 & 38.3756890439685 & 0.464310956031463 \tabularnewline
22 & 39.44 & 38.7433210130953 & 0.696678986904709 \tabularnewline
23 & 39.12 & 38.5281365968726 & 0.591863403127417 \tabularnewline
24 & 38.82 & 38.3836069730294 & 0.436393026970576 \tabularnewline
25 & 38.99 & 38.4726456275584 & 0.517354372441637 \tabularnewline
26 & 38.39 & 37.7783797867461 & 0.611620213253877 \tabularnewline
27 & 38.71 & 38.0939618428107 & 0.61603815718931 \tabularnewline
28 & 38.43 & 38.0474399584419 & 0.38256004155805 \tabularnewline
29 & 38.67 & 38.1802081889665 & 0.489791811033509 \tabularnewline
30 & 38.45 & 37.9499179060887 & 0.5000820939113 \tabularnewline
31 & 39.34 & 38.8007772301049 & 0.539222769895091 \tabularnewline
32 & 39.6 & 39.0941352173144 & 0.505864782685603 \tabularnewline
33 & 39.84 & 39.4730899337889 & 0.366910066211128 \tabularnewline
34 & 40 & 39.3683340787782 & 0.631665921221825 \tabularnewline
35 & 39.55 & 39.0281537029006 & 0.521846297099411 \tabularnewline
36 & 38.5 & 38.2080327854917 & 0.291967214508322 \tabularnewline
37 & 38.13 & 38.083213007023 & 0.0467869929769685 \tabularnewline
38 & 38.75 & 38.412191580683 & 0.337808419316968 \tabularnewline
39 & 38.2 & 37.9410412427843 & 0.258958757215679 \tabularnewline
40 & 38.39 & 38.3410658709367 & 0.0489341290633026 \tabularnewline
41 & 38.29 & 38.6322798492007 & -0.342279849200658 \tabularnewline
42 & 38.73 & 39.2582565035172 & -0.528256503517192 \tabularnewline
43 & 38.33 & 38.6107339885989 & -0.280733988598858 \tabularnewline
44 & 38.73 & 38.589098269787 & 0.140901730212967 \tabularnewline
45 & 39.06 & 38.7384845802324 & 0.321515419767622 \tabularnewline
46 & 39.28 & 39.0717380687236 & 0.208261931276415 \tabularnewline
47 & 38.6 & 38.0636787567552 & 0.536321243244774 \tabularnewline
48 & 39.68 & 39.0620455889733 & 0.617954411026714 \tabularnewline
49 & 39.61 & 38.6000198563759 & 1.00998014362407 \tabularnewline
50 & 40.74 & 39.6867409433124 & 1.05325905668763 \tabularnewline
51 & 40.55 & 39.5347012896783 & 1.01529871032175 \tabularnewline
52 & 40.8 & 40.0380042226822 & 0.761995777317837 \tabularnewline
53 & 40.81 & 39.4804395746006 & 1.32956042539938 \tabularnewline
54 & 41.47 & 40.0549169516603 & 1.41508304833973 \tabularnewline
55 & 41 & 39.9281859789812 & 1.07181402101878 \tabularnewline
56 & 41.42 & 40.3239351923144 & 1.09606480768565 \tabularnewline
57 & 41.84 & 40.6903721836767 & 1.14962781632335 \tabularnewline
58 & 40.89 & 39.8286862988382 & 1.06131370116179 \tabularnewline
59 & 41.05 & 40.10886449242 & 0.941135507579984 \tabularnewline
60 & 41.2 & 40.0790659763196 & 1.12093402368041 \tabularnewline
61 & 40.45 & 39.8202438887296 & 0.629756111270386 \tabularnewline
62 & 40.55 & 40.0737352714613 & 0.476264728538675 \tabularnewline
63 & 40.5 & 39.99510209909 & 0.504897900909978 \tabularnewline
64 & 39.23 & 38.7904693624347 & 0.439530637565318 \tabularnewline
65 & 39.42 & 38.6193543949749 & 0.800645605025125 \tabularnewline
66 & 40.05 & 39.582944200949 & 0.46705579905099 \tabularnewline
67 & 39.7 & 39.294119211003 & 0.405880788997007 \tabularnewline
68 & 39.17 & 39.1500814193908 & 0.0199185806091803 \tabularnewline
69 & 39.42 & 39.5244170520893 & -0.104417052089279 \tabularnewline
70 & 39.24 & 39.6438390209411 & -0.403839020941104 \tabularnewline
71 & 39.6 & 39.9125060778597 & -0.312506077859726 \tabularnewline
72 & 39.38 & 39.559560105952 & -0.179560105951991 \tabularnewline
73 & 39.38 & 39.5136436711806 & -0.133643671180594 \tabularnewline
74 & 39.8 & 39.8441483517715 & -0.044148351771462 \tabularnewline
75 & 40.45 & 40.4529174580921 & -0.00291745809204928 \tabularnewline
76 & 40.45 & 39.9364628469024 & 0.513537153097642 \tabularnewline
77 & 40.38 & 40.1316914399873 & 0.248308560012666 \tabularnewline
78 & 40.25 & 40.033898509185 & 0.216101490814956 \tabularnewline
79 & 40.03 & 39.8398990196364 & 0.190100980363595 \tabularnewline
80 & 40 & 39.7817931013103 & 0.218206898689692 \tabularnewline
81 & 39.76 & 39.5482086333674 & 0.211791366632625 \tabularnewline
82 & 39.96 & 39.4735669054495 & 0.486433094550538 \tabularnewline
83 & 40 & 39.758218951456 & 0.241781048544014 \tabularnewline
84 & 39.9 & 39.621067359961 & 0.278932640039034 \tabularnewline
85 & 39.76 & 39.7701716166258 & -0.0101716166258026 \tabularnewline
86 & 38.9 & 39.3185003097135 & -0.418500309713472 \tabularnewline
87 & 38.92 & 38.9532840218379 & -0.0332840218379352 \tabularnewline
88 & 37.34 & 37.3850308578525 & -0.0450308578524933 \tabularnewline
89 & 37.99 & 38.5113689252805 & -0.521368925280479 \tabularnewline
90 & 37.6 & 38.1438701789659 & -0.543870178965909 \tabularnewline
91 & 37.45 & 38.3984853121434 & -0.948485312143427 \tabularnewline
92 & 37.35 & 37.9667549418992 & -0.616754941899248 \tabularnewline
93 & 36.12 & 37.1438626987019 & -1.02386269870194 \tabularnewline
94 & 34.83 & 35.7025371145849 & -0.872537114584893 \tabularnewline
95 & 34.83 & 35.5694829177191 & -0.739482917719087 \tabularnewline
96 & 35.39 & 35.7294974182283 & -0.339497418228288 \tabularnewline
97 & 36.05 & 36.7238034868144 & -0.673803486814436 \tabularnewline
98 & 36.66 & 37.5578301153064 & -0.897830115306391 \tabularnewline
99 & 36.54 & 37.3116320497128 & -0.771632049712795 \tabularnewline
100 & 35.87 & 36.674548765642 & -0.804548765641962 \tabularnewline
101 & 36.01 & 36.6669933665758 & -0.656993366575791 \tabularnewline
102 & 36.03 & 36.6749138257867 & -0.64491382578667 \tabularnewline
103 & 35.63 & 36.0148548636681 & -0.384854863668123 \tabularnewline
104 & 36.04 & 36.1990657721949 & -0.159065772194856 \tabularnewline
105 & 35.96 & 36.4339953251341 & -0.473995325134131 \tabularnewline
106 & 35.94 & 35.8757532377608 & 0.0642467622392011 \tabularnewline
107 & 36.06 & 36.1073386921403 & -0.0473386921402804 \tabularnewline
108 & 36.52 & 36.6962936492218 & -0.176293649221777 \tabularnewline
109 & 36.91 & 37.3051701457328 & -0.395170145732774 \tabularnewline
110 & 37.05 & 37.3922836881575 & -0.342283688157542 \tabularnewline
111 & 35.98 & 37.0638027546069 & -1.08380275460693 \tabularnewline
112 & 35.5 & 36.4827433849168 & -0.982743384916835 \tabularnewline
113 & 34.04 & 34.8161374673555 & -0.776137467355515 \tabularnewline
114 & 34.2 & 34.8719404231151 & -0.67194042311508 \tabularnewline
115 & 33.63 & 34.3048608490162 & -0.67486084901619 \tabularnewline
116 & 33.84 & 34.725170743531 & -0.885170743530978 \tabularnewline
117 & 34.41 & 35.5468675815005 & -1.13686758150053 \tabularnewline
118 & 34.84 & 35.9001527786768 & -1.06015277867676 \tabularnewline
119 & 35.2 & 35.8361194220965 & -0.636119422096541 \tabularnewline
120 & 35.3 & 35.6356126590107 & -0.335612659010687 \tabularnewline
121 & 34.8 & 34.9943160006428 & -0.194316000642804 \tabularnewline
122 & 35.43 & 35.1329897773884 & 0.297010222611607 \tabularnewline
123 & 34.88 & 34.5209615805895 & 0.359038419410526 \tabularnewline
124 & 34.81 & 34.3492804161718 & 0.460719583828167 \tabularnewline
125 & 34.83 & 34.5721041046415 & 0.257895895358521 \tabularnewline
126 & 34.7 & 34.3426866493217 & 0.357313350678259 \tabularnewline
127 & 34.59 & 34.5756062915158 & 0.0143937084842081 \tabularnewline
128 & 34.77 & 34.6927080538183 & 0.0772919461816568 \tabularnewline
129 & 34.8 & 34.5251885148859 & 0.274811485114105 \tabularnewline
130 & 34.32 & 33.9804673486321 & 0.339532651367886 \tabularnewline
131 & 33.96 & 33.6231341081239 & 0.336865891876087 \tabularnewline
132 & 34 & 33.6682550101545 & 0.331744989845513 \tabularnewline
133 & 34.77 & 34.0339246778919 & 0.736075322108057 \tabularnewline
134 & 34.53 & 34.1116710028803 & 0.418328997119685 \tabularnewline
135 & 35.2 & 34.9359610517478 & 0.264038948252174 \tabularnewline
136 & 35.06 & 33.8616871184628 & 1.19831288153717 \tabularnewline
137 & 35.18 & 34.1158175253967 & 1.06418247460334 \tabularnewline
138 & 35 & 33.9319242498692 & 1.06807575013081 \tabularnewline
139 & 34.49 & 33.4884809514141 & 1.00151904858595 \tabularnewline
140 & 35.15 & 34.4571319538882 & 0.692868046111829 \tabularnewline
141 & 34.59 & 33.8320710927102 & 0.757928907289817 \tabularnewline
142 & 34.65 & 33.4500064029069 & 1.19999359709308 \tabularnewline
143 & 34.59 & 33.759510053311 & 0.830489946689001 \tabularnewline
144 & 34.92 & 34.513084532589 & 0.406915467410981 \tabularnewline
145 & 34.37 & 34.3562395197683 & 0.0137604802316702 \tabularnewline
146 & 34.47 & 34.7717115615989 & -0.301711561598928 \tabularnewline
147 & 35.13 & 35.482737474481 & -0.352737474480963 \tabularnewline
148 & 35.15 & 35.5214586015715 & -0.371458601571488 \tabularnewline
149 & 34.48 & 35.2481969279837 & -0.768196927983733 \tabularnewline
150 & 34.91 & 35.3769928468341 & -0.466992846834115 \tabularnewline
151 & 35.95 & 36.2562809409727 & -0.306280940972645 \tabularnewline
152 & 35.52 & 36.175612793105 & -0.655612793105005 \tabularnewline
153 & 36.16 & 36.6846138928611 & -0.524613892861061 \tabularnewline
154 & 36.15 & 36.6681928079624 & -0.51819280796245 \tabularnewline
155 & 36.07 & 36.6755336383239 & -0.605533638323942 \tabularnewline
156 & 36.5 & 37.1541712797169 & -0.654171279716886 \tabularnewline
157 & 36.51 & 36.7584070950347 & -0.24840709503466 \tabularnewline
158 & 36.23 & 36.6468224727105 & -0.416822472710491 \tabularnewline
159 & 35.91 & 36.0175523761325 & -0.107552376132465 \tabularnewline
160 & 35.56 & 35.5370284348011 & 0.0229715651988746 \tabularnewline
161 & 36.45 & 36.6800696561892 & -0.230069656189159 \tabularnewline
162 & 36.34 & 36.8379268328557 & -0.497926832855706 \tabularnewline
163 & 37.32 & 37.626304836063 & -0.306304836062998 \tabularnewline
164 & 37.47 & 38.2319303724758 & -0.761930372475837 \tabularnewline
165 & 36.98 & 37.2151580264646 & -0.235158026464654 \tabularnewline
166 & 36.42 & 37.0504493964686 & -0.630449396468581 \tabularnewline
167 & 37.04 & 37.9094629947669 & -0.8694629947669 \tabularnewline
168 & 37.15 & 37.7007904879194 & -0.550790487919393 \tabularnewline
169 & 37.13 & 37.6312846835723 & -0.501284683572261 \tabularnewline
170 & 38.21 & 38.6086616277641 & -0.3986616277641 \tabularnewline
171 & 37.91 & 38.5360537688835 & -0.626053768883503 \tabularnewline
172 & 38.4 & 39.6752588656356 & -1.27525886563556 \tabularnewline
173 & 39.12 & 40.4065015164438 & -1.28650151644382 \tabularnewline
174 & 38.05 & 40.0493817555957 & -1.99938175559569 \tabularnewline
175 & 37.83 & 39.6260432413294 & -1.79604324132939 \tabularnewline
176 & 38.02 & 40.3010174192673 & -2.28101741926731 \tabularnewline
177 & 38.43 & 40.7811334509192 & -2.35113345091924 \tabularnewline
178 & 40.94 & 41.1966133751042 & -0.256613375104173 \tabularnewline
179 & 40.75 & 40.9452372807163 & -0.195237280716296 \tabularnewline
180 & 41.06 & 40.9743613047906 & 0.085638695209399 \tabularnewline
181 & 41.69 & 41.7030372111097 & -0.0130372111097065 \tabularnewline
182 & 41.73 & 41.5356311120353 & 0.194368887964668 \tabularnewline
183 & 42.34 & 42.2927371503803 & 0.0472628496197313 \tabularnewline
184 & 42.54 & 42.8394913926692 & -0.299491392669207 \tabularnewline
185 & 42.5 & 42.93775253839 & -0.437752538389977 \tabularnewline
186 & 42.78 & 42.8477283497125 & -0.0677283497125115 \tabularnewline
187 & 42.65 & 42.6181059039421 & 0.0318940960579113 \tabularnewline
188 & 42 & 41.9522713333077 & 0.0477286666922579 \tabularnewline
189 & 42.3 & 41.934108823591 & 0.365891176409037 \tabularnewline
190 & 42.02 & 41.7751754522128 & 0.244824547787174 \tabularnewline
191 & 41.52 & 40.7791232422156 & 0.740876757784428 \tabularnewline
192 & 41.77 & 40.4096730688809 & 1.36032693111909 \tabularnewline
193 & 42.43 & 41.8848011111105 & 0.545198888889499 \tabularnewline
194 & 42.43 & 42.0634613196955 & 0.366538680304508 \tabularnewline
195 & 42.48 & 41.9614677234442 & 0.518532276555823 \tabularnewline
196 & 42.01 & 41.4551988693233 & 0.554801130676717 \tabularnewline
197 & 41.99 & 41.6047915790674 & 0.385208420932651 \tabularnewline
198 & 42.01 & 41.3852524501849 & 0.624747549815137 \tabularnewline
199 & 42.05 & 41.6841917891375 & 0.36580821086249 \tabularnewline
200 & 41.84 & 41.4990211208246 & 0.340978879175403 \tabularnewline
201 & 41.79 & 41.5796486320835 & 0.21035136791648 \tabularnewline
202 & 41.82 & 41.6579758495184 & 0.162024150481613 \tabularnewline
203 & 41.87 & 41.6224368469529 & 0.247563153047142 \tabularnewline
204 & 41.66 & 41.4293132578288 & 0.230686742171239 \tabularnewline
205 & 41.19 & 40.9001776495847 & 0.28982235041528 \tabularnewline
206 & 40.99 & 40.993857495366 & -0.00385749536600836 \tabularnewline
207 & 41.15 & 40.7398466439612 & 0.410153356038757 \tabularnewline
208 & 40.95 & 41.0440301216364 & -0.0940301216363869 \tabularnewline
209 & 40.67 & 41.0008904103083 & -0.330890410308265 \tabularnewline
210 & 41.1 & 41.4330834210091 & -0.333083421009131 \tabularnewline
211 & 40.88 & 41.2305999202436 & -0.350599920243619 \tabularnewline
212 & 40.93 & 41.2699824006978 & -0.339982400697815 \tabularnewline
213 & 40.89 & 41.4136167023239 & -0.523616702323936 \tabularnewline
214 & 40.97 & 41.7940040949736 & -0.824004094973604 \tabularnewline
215 & 40.87 & 41.2529563282092 & -0.382956328209159 \tabularnewline
216 & 40.56 & 41.1154498933449 & -0.555449893344855 \tabularnewline
217 & 40.47 & 40.359212447934 & 0.110787552066026 \tabularnewline
218 & 40.01 & 39.8701730233252 & 0.139826976674762 \tabularnewline
219 & 40.23 & 40.5848916130254 & -0.354891613025404 \tabularnewline
220 & 40.45 & 41.0273376029699 & -0.577337602969928 \tabularnewline
221 & 40.3 & 40.6533923731907 & -0.353392373190656 \tabularnewline
222 & 40.38 & 40.7724920381345 & -0.392492038134522 \tabularnewline
223 & 39.95 & 40.9175618847197 & -0.967561884719713 \tabularnewline
224 & 39.74 & 40.52544494108 & -0.78544494108004 \tabularnewline
225 & 40.37 & 40.677385296735 & -0.307385296735008 \tabularnewline
226 & 40.05 & 40.0812853036733 & -0.0312853036733374 \tabularnewline
227 & 40.14 & 40.1159005750123 & 0.0240994249877138 \tabularnewline
228 & 39.42 & 39.654896564177 & -0.234896564177019 \tabularnewline
229 & 38.97 & 39.388419383664 & -0.418419383664045 \tabularnewline
230 & 39.06 & 39.3898655751324 & -0.329865575132395 \tabularnewline
231 & 39.86 & 39.3650967721108 & 0.494903227889226 \tabularnewline
232 & 40.49 & 39.3011767163743 & 1.18882328362575 \tabularnewline
233 & 39.99 & 38.7771157716837 & 1.21288422831627 \tabularnewline
234 & 39.94 & 38.6654645224321 & 1.27453547756793 \tabularnewline
235 & 39.97 & 38.7418697482751 & 1.22813025172486 \tabularnewline
236 & 40.21 & 39.5265460518068 & 0.683453948193185 \tabularnewline
237 & 40.39 & 39.9016793503522 & 0.488320649647805 \tabularnewline
238 & 39.95 & 39.5895958750693 & 0.360404124930749 \tabularnewline
239 & 39.46 & 39.0353401130767 & 0.424659886923292 \tabularnewline
240 & 39.07 & 38.8468815523647 & 0.22311844763525 \tabularnewline
241 & 38.64 & 38.2298997709415 & 0.410100229058537 \tabularnewline
242 & 38.96 & 38.488485845439 & 0.471514154560983 \tabularnewline
243 & 38.57 & 38.2638105690919 & 0.306189430908143 \tabularnewline
244 & 37.84 & 37.8758200903928 & -0.0358200903927714 \tabularnewline
245 & 37.36 & 37.3408842544609 & 0.0191157455390873 \tabularnewline
246 & 37.08 & 37.657019621127 & -0.577019621127017 \tabularnewline
247 & 36.45 & 36.6675715751736 & -0.217571575173601 \tabularnewline
248 & 37.02 & 36.545931877985 & 0.474068122014966 \tabularnewline
249 & 37.68 & 36.7975535071285 & 0.882446492871483 \tabularnewline
250 & 37.67 & 36.4445993586432 & 1.2254006413568 \tabularnewline
251 & 38.55 & 37.5759636553129 & 0.974036344687142 \tabularnewline
252 & 38.16 & 37.6235814728451 & 0.536418527154871 \tabularnewline
253 & 38.96 & 38.5265964310868 & 0.433403568913243 \tabularnewline
254 & 38.05 & 37.7483052288382 & 0.301694771161758 \tabularnewline
255 & 38.77 & 38.5869600102069 & 0.183039989793133 \tabularnewline
256 & 38.76 & 38.5706278931745 & 0.189372106825531 \tabularnewline
257 & 38.86 & 38.7284084311611 & 0.131591568838847 \tabularnewline
258 & 38.49 & 38.3220031477918 & 0.167996852208212 \tabularnewline
259 & 38.29 & 37.9398776101698 & 0.350122389830249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]38.58[/C][C]39.7689232306809[/C][C]-1.1889232306809[/C][/ROW]
[ROW][C]2[/C][C]38.48[/C][C]39.6740242249035[/C][C]-1.19402422490347[/C][/ROW]
[ROW][C]3[/C][C]38.56[/C][C]39.8128386134993[/C][C]-1.2528386134993[/C][/ROW]
[ROW][C]4[/C][C]38.25[/C][C]39.1081196102394[/C][C]-0.858119610239446[/C][/ROW]
[ROW][C]5[/C][C]37.97[/C][C]38.8783360006117[/C][C]-0.90833600061169[/C][/ROW]
[ROW][C]6[/C][C]38.42[/C][C]38.9119332028039[/C][C]-0.491933202803883[/C][/ROW]
[ROW][C]7[/C][C]38.6[/C][C]39.3100019543366[/C][C]-0.710001954336552[/C][/ROW]
[ROW][C]8[/C][C]38.3[/C][C]39.0128074330144[/C][C]-0.712807433014432[/C][/ROW]
[ROW][C]9[/C][C]38.22[/C][C]38.797295864792[/C][C]-0.577295864792031[/C][/ROW]
[ROW][C]10[/C][C]38.22[/C][C]38.5243480396675[/C][C]-0.304348039667498[/C][/ROW]
[ROW][C]11[/C][C]38.22[/C][C]38.3422642330419[/C][C]-0.122264233041943[/C][/ROW]
[ROW][C]12[/C][C]36.98[/C][C]37.2085435185907[/C][C]-0.22854351859069[/C][/ROW]
[ROW][C]13[/C][C]37.43[/C][C]37.8188197610727[/C][C]-0.388819761072668[/C][/ROW]
[ROW][C]14[/C][C]37.52[/C][C]37.8749669781264[/C][C]-0.354966978126353[/C][/ROW]
[ROW][C]15[/C][C]37.98[/C][C]38.1868833988012[/C][C]-0.206883398801212[/C][/ROW]
[ROW][C]16[/C][C]37.83[/C][C]37.8491348185152[/C][C]-0.0191348185152236[/C][/ROW]
[ROW][C]17[/C][C]38[/C][C]38.0838785250013[/C][C]-0.0838785250012611[/C][/ROW]
[ROW][C]18[/C][C]37.7[/C][C]37.8028170905511[/C][C]-0.10281709055111[/C][/ROW]
[ROW][C]19[/C][C]37.88[/C][C]37.8673454222654[/C][C]0.0126545777346172[/C][/ROW]
[ROW][C]20[/C][C]39.02[/C][C]38.7125295284465[/C][C]0.307470471553539[/C][/ROW]
[ROW][C]21[/C][C]38.84[/C][C]38.3756890439685[/C][C]0.464310956031463[/C][/ROW]
[ROW][C]22[/C][C]39.44[/C][C]38.7433210130953[/C][C]0.696678986904709[/C][/ROW]
[ROW][C]23[/C][C]39.12[/C][C]38.5281365968726[/C][C]0.591863403127417[/C][/ROW]
[ROW][C]24[/C][C]38.82[/C][C]38.3836069730294[/C][C]0.436393026970576[/C][/ROW]
[ROW][C]25[/C][C]38.99[/C][C]38.4726456275584[/C][C]0.517354372441637[/C][/ROW]
[ROW][C]26[/C][C]38.39[/C][C]37.7783797867461[/C][C]0.611620213253877[/C][/ROW]
[ROW][C]27[/C][C]38.71[/C][C]38.0939618428107[/C][C]0.61603815718931[/C][/ROW]
[ROW][C]28[/C][C]38.43[/C][C]38.0474399584419[/C][C]0.38256004155805[/C][/ROW]
[ROW][C]29[/C][C]38.67[/C][C]38.1802081889665[/C][C]0.489791811033509[/C][/ROW]
[ROW][C]30[/C][C]38.45[/C][C]37.9499179060887[/C][C]0.5000820939113[/C][/ROW]
[ROW][C]31[/C][C]39.34[/C][C]38.8007772301049[/C][C]0.539222769895091[/C][/ROW]
[ROW][C]32[/C][C]39.6[/C][C]39.0941352173144[/C][C]0.505864782685603[/C][/ROW]
[ROW][C]33[/C][C]39.84[/C][C]39.4730899337889[/C][C]0.366910066211128[/C][/ROW]
[ROW][C]34[/C][C]40[/C][C]39.3683340787782[/C][C]0.631665921221825[/C][/ROW]
[ROW][C]35[/C][C]39.55[/C][C]39.0281537029006[/C][C]0.521846297099411[/C][/ROW]
[ROW][C]36[/C][C]38.5[/C][C]38.2080327854917[/C][C]0.291967214508322[/C][/ROW]
[ROW][C]37[/C][C]38.13[/C][C]38.083213007023[/C][C]0.0467869929769685[/C][/ROW]
[ROW][C]38[/C][C]38.75[/C][C]38.412191580683[/C][C]0.337808419316968[/C][/ROW]
[ROW][C]39[/C][C]38.2[/C][C]37.9410412427843[/C][C]0.258958757215679[/C][/ROW]
[ROW][C]40[/C][C]38.39[/C][C]38.3410658709367[/C][C]0.0489341290633026[/C][/ROW]
[ROW][C]41[/C][C]38.29[/C][C]38.6322798492007[/C][C]-0.342279849200658[/C][/ROW]
[ROW][C]42[/C][C]38.73[/C][C]39.2582565035172[/C][C]-0.528256503517192[/C][/ROW]
[ROW][C]43[/C][C]38.33[/C][C]38.6107339885989[/C][C]-0.280733988598858[/C][/ROW]
[ROW][C]44[/C][C]38.73[/C][C]38.589098269787[/C][C]0.140901730212967[/C][/ROW]
[ROW][C]45[/C][C]39.06[/C][C]38.7384845802324[/C][C]0.321515419767622[/C][/ROW]
[ROW][C]46[/C][C]39.28[/C][C]39.0717380687236[/C][C]0.208261931276415[/C][/ROW]
[ROW][C]47[/C][C]38.6[/C][C]38.0636787567552[/C][C]0.536321243244774[/C][/ROW]
[ROW][C]48[/C][C]39.68[/C][C]39.0620455889733[/C][C]0.617954411026714[/C][/ROW]
[ROW][C]49[/C][C]39.61[/C][C]38.6000198563759[/C][C]1.00998014362407[/C][/ROW]
[ROW][C]50[/C][C]40.74[/C][C]39.6867409433124[/C][C]1.05325905668763[/C][/ROW]
[ROW][C]51[/C][C]40.55[/C][C]39.5347012896783[/C][C]1.01529871032175[/C][/ROW]
[ROW][C]52[/C][C]40.8[/C][C]40.0380042226822[/C][C]0.761995777317837[/C][/ROW]
[ROW][C]53[/C][C]40.81[/C][C]39.4804395746006[/C][C]1.32956042539938[/C][/ROW]
[ROW][C]54[/C][C]41.47[/C][C]40.0549169516603[/C][C]1.41508304833973[/C][/ROW]
[ROW][C]55[/C][C]41[/C][C]39.9281859789812[/C][C]1.07181402101878[/C][/ROW]
[ROW][C]56[/C][C]41.42[/C][C]40.3239351923144[/C][C]1.09606480768565[/C][/ROW]
[ROW][C]57[/C][C]41.84[/C][C]40.6903721836767[/C][C]1.14962781632335[/C][/ROW]
[ROW][C]58[/C][C]40.89[/C][C]39.8286862988382[/C][C]1.06131370116179[/C][/ROW]
[ROW][C]59[/C][C]41.05[/C][C]40.10886449242[/C][C]0.941135507579984[/C][/ROW]
[ROW][C]60[/C][C]41.2[/C][C]40.0790659763196[/C][C]1.12093402368041[/C][/ROW]
[ROW][C]61[/C][C]40.45[/C][C]39.8202438887296[/C][C]0.629756111270386[/C][/ROW]
[ROW][C]62[/C][C]40.55[/C][C]40.0737352714613[/C][C]0.476264728538675[/C][/ROW]
[ROW][C]63[/C][C]40.5[/C][C]39.99510209909[/C][C]0.504897900909978[/C][/ROW]
[ROW][C]64[/C][C]39.23[/C][C]38.7904693624347[/C][C]0.439530637565318[/C][/ROW]
[ROW][C]65[/C][C]39.42[/C][C]38.6193543949749[/C][C]0.800645605025125[/C][/ROW]
[ROW][C]66[/C][C]40.05[/C][C]39.582944200949[/C][C]0.46705579905099[/C][/ROW]
[ROW][C]67[/C][C]39.7[/C][C]39.294119211003[/C][C]0.405880788997007[/C][/ROW]
[ROW][C]68[/C][C]39.17[/C][C]39.1500814193908[/C][C]0.0199185806091803[/C][/ROW]
[ROW][C]69[/C][C]39.42[/C][C]39.5244170520893[/C][C]-0.104417052089279[/C][/ROW]
[ROW][C]70[/C][C]39.24[/C][C]39.6438390209411[/C][C]-0.403839020941104[/C][/ROW]
[ROW][C]71[/C][C]39.6[/C][C]39.9125060778597[/C][C]-0.312506077859726[/C][/ROW]
[ROW][C]72[/C][C]39.38[/C][C]39.559560105952[/C][C]-0.179560105951991[/C][/ROW]
[ROW][C]73[/C][C]39.38[/C][C]39.5136436711806[/C][C]-0.133643671180594[/C][/ROW]
[ROW][C]74[/C][C]39.8[/C][C]39.8441483517715[/C][C]-0.044148351771462[/C][/ROW]
[ROW][C]75[/C][C]40.45[/C][C]40.4529174580921[/C][C]-0.00291745809204928[/C][/ROW]
[ROW][C]76[/C][C]40.45[/C][C]39.9364628469024[/C][C]0.513537153097642[/C][/ROW]
[ROW][C]77[/C][C]40.38[/C][C]40.1316914399873[/C][C]0.248308560012666[/C][/ROW]
[ROW][C]78[/C][C]40.25[/C][C]40.033898509185[/C][C]0.216101490814956[/C][/ROW]
[ROW][C]79[/C][C]40.03[/C][C]39.8398990196364[/C][C]0.190100980363595[/C][/ROW]
[ROW][C]80[/C][C]40[/C][C]39.7817931013103[/C][C]0.218206898689692[/C][/ROW]
[ROW][C]81[/C][C]39.76[/C][C]39.5482086333674[/C][C]0.211791366632625[/C][/ROW]
[ROW][C]82[/C][C]39.96[/C][C]39.4735669054495[/C][C]0.486433094550538[/C][/ROW]
[ROW][C]83[/C][C]40[/C][C]39.758218951456[/C][C]0.241781048544014[/C][/ROW]
[ROW][C]84[/C][C]39.9[/C][C]39.621067359961[/C][C]0.278932640039034[/C][/ROW]
[ROW][C]85[/C][C]39.76[/C][C]39.7701716166258[/C][C]-0.0101716166258026[/C][/ROW]
[ROW][C]86[/C][C]38.9[/C][C]39.3185003097135[/C][C]-0.418500309713472[/C][/ROW]
[ROW][C]87[/C][C]38.92[/C][C]38.9532840218379[/C][C]-0.0332840218379352[/C][/ROW]
[ROW][C]88[/C][C]37.34[/C][C]37.3850308578525[/C][C]-0.0450308578524933[/C][/ROW]
[ROW][C]89[/C][C]37.99[/C][C]38.5113689252805[/C][C]-0.521368925280479[/C][/ROW]
[ROW][C]90[/C][C]37.6[/C][C]38.1438701789659[/C][C]-0.543870178965909[/C][/ROW]
[ROW][C]91[/C][C]37.45[/C][C]38.3984853121434[/C][C]-0.948485312143427[/C][/ROW]
[ROW][C]92[/C][C]37.35[/C][C]37.9667549418992[/C][C]-0.616754941899248[/C][/ROW]
[ROW][C]93[/C][C]36.12[/C][C]37.1438626987019[/C][C]-1.02386269870194[/C][/ROW]
[ROW][C]94[/C][C]34.83[/C][C]35.7025371145849[/C][C]-0.872537114584893[/C][/ROW]
[ROW][C]95[/C][C]34.83[/C][C]35.5694829177191[/C][C]-0.739482917719087[/C][/ROW]
[ROW][C]96[/C][C]35.39[/C][C]35.7294974182283[/C][C]-0.339497418228288[/C][/ROW]
[ROW][C]97[/C][C]36.05[/C][C]36.7238034868144[/C][C]-0.673803486814436[/C][/ROW]
[ROW][C]98[/C][C]36.66[/C][C]37.5578301153064[/C][C]-0.897830115306391[/C][/ROW]
[ROW][C]99[/C][C]36.54[/C][C]37.3116320497128[/C][C]-0.771632049712795[/C][/ROW]
[ROW][C]100[/C][C]35.87[/C][C]36.674548765642[/C][C]-0.804548765641962[/C][/ROW]
[ROW][C]101[/C][C]36.01[/C][C]36.6669933665758[/C][C]-0.656993366575791[/C][/ROW]
[ROW][C]102[/C][C]36.03[/C][C]36.6749138257867[/C][C]-0.64491382578667[/C][/ROW]
[ROW][C]103[/C][C]35.63[/C][C]36.0148548636681[/C][C]-0.384854863668123[/C][/ROW]
[ROW][C]104[/C][C]36.04[/C][C]36.1990657721949[/C][C]-0.159065772194856[/C][/ROW]
[ROW][C]105[/C][C]35.96[/C][C]36.4339953251341[/C][C]-0.473995325134131[/C][/ROW]
[ROW][C]106[/C][C]35.94[/C][C]35.8757532377608[/C][C]0.0642467622392011[/C][/ROW]
[ROW][C]107[/C][C]36.06[/C][C]36.1073386921403[/C][C]-0.0473386921402804[/C][/ROW]
[ROW][C]108[/C][C]36.52[/C][C]36.6962936492218[/C][C]-0.176293649221777[/C][/ROW]
[ROW][C]109[/C][C]36.91[/C][C]37.3051701457328[/C][C]-0.395170145732774[/C][/ROW]
[ROW][C]110[/C][C]37.05[/C][C]37.3922836881575[/C][C]-0.342283688157542[/C][/ROW]
[ROW][C]111[/C][C]35.98[/C][C]37.0638027546069[/C][C]-1.08380275460693[/C][/ROW]
[ROW][C]112[/C][C]35.5[/C][C]36.4827433849168[/C][C]-0.982743384916835[/C][/ROW]
[ROW][C]113[/C][C]34.04[/C][C]34.8161374673555[/C][C]-0.776137467355515[/C][/ROW]
[ROW][C]114[/C][C]34.2[/C][C]34.8719404231151[/C][C]-0.67194042311508[/C][/ROW]
[ROW][C]115[/C][C]33.63[/C][C]34.3048608490162[/C][C]-0.67486084901619[/C][/ROW]
[ROW][C]116[/C][C]33.84[/C][C]34.725170743531[/C][C]-0.885170743530978[/C][/ROW]
[ROW][C]117[/C][C]34.41[/C][C]35.5468675815005[/C][C]-1.13686758150053[/C][/ROW]
[ROW][C]118[/C][C]34.84[/C][C]35.9001527786768[/C][C]-1.06015277867676[/C][/ROW]
[ROW][C]119[/C][C]35.2[/C][C]35.8361194220965[/C][C]-0.636119422096541[/C][/ROW]
[ROW][C]120[/C][C]35.3[/C][C]35.6356126590107[/C][C]-0.335612659010687[/C][/ROW]
[ROW][C]121[/C][C]34.8[/C][C]34.9943160006428[/C][C]-0.194316000642804[/C][/ROW]
[ROW][C]122[/C][C]35.43[/C][C]35.1329897773884[/C][C]0.297010222611607[/C][/ROW]
[ROW][C]123[/C][C]34.88[/C][C]34.5209615805895[/C][C]0.359038419410526[/C][/ROW]
[ROW][C]124[/C][C]34.81[/C][C]34.3492804161718[/C][C]0.460719583828167[/C][/ROW]
[ROW][C]125[/C][C]34.83[/C][C]34.5721041046415[/C][C]0.257895895358521[/C][/ROW]
[ROW][C]126[/C][C]34.7[/C][C]34.3426866493217[/C][C]0.357313350678259[/C][/ROW]
[ROW][C]127[/C][C]34.59[/C][C]34.5756062915158[/C][C]0.0143937084842081[/C][/ROW]
[ROW][C]128[/C][C]34.77[/C][C]34.6927080538183[/C][C]0.0772919461816568[/C][/ROW]
[ROW][C]129[/C][C]34.8[/C][C]34.5251885148859[/C][C]0.274811485114105[/C][/ROW]
[ROW][C]130[/C][C]34.32[/C][C]33.9804673486321[/C][C]0.339532651367886[/C][/ROW]
[ROW][C]131[/C][C]33.96[/C][C]33.6231341081239[/C][C]0.336865891876087[/C][/ROW]
[ROW][C]132[/C][C]34[/C][C]33.6682550101545[/C][C]0.331744989845513[/C][/ROW]
[ROW][C]133[/C][C]34.77[/C][C]34.0339246778919[/C][C]0.736075322108057[/C][/ROW]
[ROW][C]134[/C][C]34.53[/C][C]34.1116710028803[/C][C]0.418328997119685[/C][/ROW]
[ROW][C]135[/C][C]35.2[/C][C]34.9359610517478[/C][C]0.264038948252174[/C][/ROW]
[ROW][C]136[/C][C]35.06[/C][C]33.8616871184628[/C][C]1.19831288153717[/C][/ROW]
[ROW][C]137[/C][C]35.18[/C][C]34.1158175253967[/C][C]1.06418247460334[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]33.9319242498692[/C][C]1.06807575013081[/C][/ROW]
[ROW][C]139[/C][C]34.49[/C][C]33.4884809514141[/C][C]1.00151904858595[/C][/ROW]
[ROW][C]140[/C][C]35.15[/C][C]34.4571319538882[/C][C]0.692868046111829[/C][/ROW]
[ROW][C]141[/C][C]34.59[/C][C]33.8320710927102[/C][C]0.757928907289817[/C][/ROW]
[ROW][C]142[/C][C]34.65[/C][C]33.4500064029069[/C][C]1.19999359709308[/C][/ROW]
[ROW][C]143[/C][C]34.59[/C][C]33.759510053311[/C][C]0.830489946689001[/C][/ROW]
[ROW][C]144[/C][C]34.92[/C][C]34.513084532589[/C][C]0.406915467410981[/C][/ROW]
[ROW][C]145[/C][C]34.37[/C][C]34.3562395197683[/C][C]0.0137604802316702[/C][/ROW]
[ROW][C]146[/C][C]34.47[/C][C]34.7717115615989[/C][C]-0.301711561598928[/C][/ROW]
[ROW][C]147[/C][C]35.13[/C][C]35.482737474481[/C][C]-0.352737474480963[/C][/ROW]
[ROW][C]148[/C][C]35.15[/C][C]35.5214586015715[/C][C]-0.371458601571488[/C][/ROW]
[ROW][C]149[/C][C]34.48[/C][C]35.2481969279837[/C][C]-0.768196927983733[/C][/ROW]
[ROW][C]150[/C][C]34.91[/C][C]35.3769928468341[/C][C]-0.466992846834115[/C][/ROW]
[ROW][C]151[/C][C]35.95[/C][C]36.2562809409727[/C][C]-0.306280940972645[/C][/ROW]
[ROW][C]152[/C][C]35.52[/C][C]36.175612793105[/C][C]-0.655612793105005[/C][/ROW]
[ROW][C]153[/C][C]36.16[/C][C]36.6846138928611[/C][C]-0.524613892861061[/C][/ROW]
[ROW][C]154[/C][C]36.15[/C][C]36.6681928079624[/C][C]-0.51819280796245[/C][/ROW]
[ROW][C]155[/C][C]36.07[/C][C]36.6755336383239[/C][C]-0.605533638323942[/C][/ROW]
[ROW][C]156[/C][C]36.5[/C][C]37.1541712797169[/C][C]-0.654171279716886[/C][/ROW]
[ROW][C]157[/C][C]36.51[/C][C]36.7584070950347[/C][C]-0.24840709503466[/C][/ROW]
[ROW][C]158[/C][C]36.23[/C][C]36.6468224727105[/C][C]-0.416822472710491[/C][/ROW]
[ROW][C]159[/C][C]35.91[/C][C]36.0175523761325[/C][C]-0.107552376132465[/C][/ROW]
[ROW][C]160[/C][C]35.56[/C][C]35.5370284348011[/C][C]0.0229715651988746[/C][/ROW]
[ROW][C]161[/C][C]36.45[/C][C]36.6800696561892[/C][C]-0.230069656189159[/C][/ROW]
[ROW][C]162[/C][C]36.34[/C][C]36.8379268328557[/C][C]-0.497926832855706[/C][/ROW]
[ROW][C]163[/C][C]37.32[/C][C]37.626304836063[/C][C]-0.306304836062998[/C][/ROW]
[ROW][C]164[/C][C]37.47[/C][C]38.2319303724758[/C][C]-0.761930372475837[/C][/ROW]
[ROW][C]165[/C][C]36.98[/C][C]37.2151580264646[/C][C]-0.235158026464654[/C][/ROW]
[ROW][C]166[/C][C]36.42[/C][C]37.0504493964686[/C][C]-0.630449396468581[/C][/ROW]
[ROW][C]167[/C][C]37.04[/C][C]37.9094629947669[/C][C]-0.8694629947669[/C][/ROW]
[ROW][C]168[/C][C]37.15[/C][C]37.7007904879194[/C][C]-0.550790487919393[/C][/ROW]
[ROW][C]169[/C][C]37.13[/C][C]37.6312846835723[/C][C]-0.501284683572261[/C][/ROW]
[ROW][C]170[/C][C]38.21[/C][C]38.6086616277641[/C][C]-0.3986616277641[/C][/ROW]
[ROW][C]171[/C][C]37.91[/C][C]38.5360537688835[/C][C]-0.626053768883503[/C][/ROW]
[ROW][C]172[/C][C]38.4[/C][C]39.6752588656356[/C][C]-1.27525886563556[/C][/ROW]
[ROW][C]173[/C][C]39.12[/C][C]40.4065015164438[/C][C]-1.28650151644382[/C][/ROW]
[ROW][C]174[/C][C]38.05[/C][C]40.0493817555957[/C][C]-1.99938175559569[/C][/ROW]
[ROW][C]175[/C][C]37.83[/C][C]39.6260432413294[/C][C]-1.79604324132939[/C][/ROW]
[ROW][C]176[/C][C]38.02[/C][C]40.3010174192673[/C][C]-2.28101741926731[/C][/ROW]
[ROW][C]177[/C][C]38.43[/C][C]40.7811334509192[/C][C]-2.35113345091924[/C][/ROW]
[ROW][C]178[/C][C]40.94[/C][C]41.1966133751042[/C][C]-0.256613375104173[/C][/ROW]
[ROW][C]179[/C][C]40.75[/C][C]40.9452372807163[/C][C]-0.195237280716296[/C][/ROW]
[ROW][C]180[/C][C]41.06[/C][C]40.9743613047906[/C][C]0.085638695209399[/C][/ROW]
[ROW][C]181[/C][C]41.69[/C][C]41.7030372111097[/C][C]-0.0130372111097065[/C][/ROW]
[ROW][C]182[/C][C]41.73[/C][C]41.5356311120353[/C][C]0.194368887964668[/C][/ROW]
[ROW][C]183[/C][C]42.34[/C][C]42.2927371503803[/C][C]0.0472628496197313[/C][/ROW]
[ROW][C]184[/C][C]42.54[/C][C]42.8394913926692[/C][C]-0.299491392669207[/C][/ROW]
[ROW][C]185[/C][C]42.5[/C][C]42.93775253839[/C][C]-0.437752538389977[/C][/ROW]
[ROW][C]186[/C][C]42.78[/C][C]42.8477283497125[/C][C]-0.0677283497125115[/C][/ROW]
[ROW][C]187[/C][C]42.65[/C][C]42.6181059039421[/C][C]0.0318940960579113[/C][/ROW]
[ROW][C]188[/C][C]42[/C][C]41.9522713333077[/C][C]0.0477286666922579[/C][/ROW]
[ROW][C]189[/C][C]42.3[/C][C]41.934108823591[/C][C]0.365891176409037[/C][/ROW]
[ROW][C]190[/C][C]42.02[/C][C]41.7751754522128[/C][C]0.244824547787174[/C][/ROW]
[ROW][C]191[/C][C]41.52[/C][C]40.7791232422156[/C][C]0.740876757784428[/C][/ROW]
[ROW][C]192[/C][C]41.77[/C][C]40.4096730688809[/C][C]1.36032693111909[/C][/ROW]
[ROW][C]193[/C][C]42.43[/C][C]41.8848011111105[/C][C]0.545198888889499[/C][/ROW]
[ROW][C]194[/C][C]42.43[/C][C]42.0634613196955[/C][C]0.366538680304508[/C][/ROW]
[ROW][C]195[/C][C]42.48[/C][C]41.9614677234442[/C][C]0.518532276555823[/C][/ROW]
[ROW][C]196[/C][C]42.01[/C][C]41.4551988693233[/C][C]0.554801130676717[/C][/ROW]
[ROW][C]197[/C][C]41.99[/C][C]41.6047915790674[/C][C]0.385208420932651[/C][/ROW]
[ROW][C]198[/C][C]42.01[/C][C]41.3852524501849[/C][C]0.624747549815137[/C][/ROW]
[ROW][C]199[/C][C]42.05[/C][C]41.6841917891375[/C][C]0.36580821086249[/C][/ROW]
[ROW][C]200[/C][C]41.84[/C][C]41.4990211208246[/C][C]0.340978879175403[/C][/ROW]
[ROW][C]201[/C][C]41.79[/C][C]41.5796486320835[/C][C]0.21035136791648[/C][/ROW]
[ROW][C]202[/C][C]41.82[/C][C]41.6579758495184[/C][C]0.162024150481613[/C][/ROW]
[ROW][C]203[/C][C]41.87[/C][C]41.6224368469529[/C][C]0.247563153047142[/C][/ROW]
[ROW][C]204[/C][C]41.66[/C][C]41.4293132578288[/C][C]0.230686742171239[/C][/ROW]
[ROW][C]205[/C][C]41.19[/C][C]40.9001776495847[/C][C]0.28982235041528[/C][/ROW]
[ROW][C]206[/C][C]40.99[/C][C]40.993857495366[/C][C]-0.00385749536600836[/C][/ROW]
[ROW][C]207[/C][C]41.15[/C][C]40.7398466439612[/C][C]0.410153356038757[/C][/ROW]
[ROW][C]208[/C][C]40.95[/C][C]41.0440301216364[/C][C]-0.0940301216363869[/C][/ROW]
[ROW][C]209[/C][C]40.67[/C][C]41.0008904103083[/C][C]-0.330890410308265[/C][/ROW]
[ROW][C]210[/C][C]41.1[/C][C]41.4330834210091[/C][C]-0.333083421009131[/C][/ROW]
[ROW][C]211[/C][C]40.88[/C][C]41.2305999202436[/C][C]-0.350599920243619[/C][/ROW]
[ROW][C]212[/C][C]40.93[/C][C]41.2699824006978[/C][C]-0.339982400697815[/C][/ROW]
[ROW][C]213[/C][C]40.89[/C][C]41.4136167023239[/C][C]-0.523616702323936[/C][/ROW]
[ROW][C]214[/C][C]40.97[/C][C]41.7940040949736[/C][C]-0.824004094973604[/C][/ROW]
[ROW][C]215[/C][C]40.87[/C][C]41.2529563282092[/C][C]-0.382956328209159[/C][/ROW]
[ROW][C]216[/C][C]40.56[/C][C]41.1154498933449[/C][C]-0.555449893344855[/C][/ROW]
[ROW][C]217[/C][C]40.47[/C][C]40.359212447934[/C][C]0.110787552066026[/C][/ROW]
[ROW][C]218[/C][C]40.01[/C][C]39.8701730233252[/C][C]0.139826976674762[/C][/ROW]
[ROW][C]219[/C][C]40.23[/C][C]40.5848916130254[/C][C]-0.354891613025404[/C][/ROW]
[ROW][C]220[/C][C]40.45[/C][C]41.0273376029699[/C][C]-0.577337602969928[/C][/ROW]
[ROW][C]221[/C][C]40.3[/C][C]40.6533923731907[/C][C]-0.353392373190656[/C][/ROW]
[ROW][C]222[/C][C]40.38[/C][C]40.7724920381345[/C][C]-0.392492038134522[/C][/ROW]
[ROW][C]223[/C][C]39.95[/C][C]40.9175618847197[/C][C]-0.967561884719713[/C][/ROW]
[ROW][C]224[/C][C]39.74[/C][C]40.52544494108[/C][C]-0.78544494108004[/C][/ROW]
[ROW][C]225[/C][C]40.37[/C][C]40.677385296735[/C][C]-0.307385296735008[/C][/ROW]
[ROW][C]226[/C][C]40.05[/C][C]40.0812853036733[/C][C]-0.0312853036733374[/C][/ROW]
[ROW][C]227[/C][C]40.14[/C][C]40.1159005750123[/C][C]0.0240994249877138[/C][/ROW]
[ROW][C]228[/C][C]39.42[/C][C]39.654896564177[/C][C]-0.234896564177019[/C][/ROW]
[ROW][C]229[/C][C]38.97[/C][C]39.388419383664[/C][C]-0.418419383664045[/C][/ROW]
[ROW][C]230[/C][C]39.06[/C][C]39.3898655751324[/C][C]-0.329865575132395[/C][/ROW]
[ROW][C]231[/C][C]39.86[/C][C]39.3650967721108[/C][C]0.494903227889226[/C][/ROW]
[ROW][C]232[/C][C]40.49[/C][C]39.3011767163743[/C][C]1.18882328362575[/C][/ROW]
[ROW][C]233[/C][C]39.99[/C][C]38.7771157716837[/C][C]1.21288422831627[/C][/ROW]
[ROW][C]234[/C][C]39.94[/C][C]38.6654645224321[/C][C]1.27453547756793[/C][/ROW]
[ROW][C]235[/C][C]39.97[/C][C]38.7418697482751[/C][C]1.22813025172486[/C][/ROW]
[ROW][C]236[/C][C]40.21[/C][C]39.5265460518068[/C][C]0.683453948193185[/C][/ROW]
[ROW][C]237[/C][C]40.39[/C][C]39.9016793503522[/C][C]0.488320649647805[/C][/ROW]
[ROW][C]238[/C][C]39.95[/C][C]39.5895958750693[/C][C]0.360404124930749[/C][/ROW]
[ROW][C]239[/C][C]39.46[/C][C]39.0353401130767[/C][C]0.424659886923292[/C][/ROW]
[ROW][C]240[/C][C]39.07[/C][C]38.8468815523647[/C][C]0.22311844763525[/C][/ROW]
[ROW][C]241[/C][C]38.64[/C][C]38.2298997709415[/C][C]0.410100229058537[/C][/ROW]
[ROW][C]242[/C][C]38.96[/C][C]38.488485845439[/C][C]0.471514154560983[/C][/ROW]
[ROW][C]243[/C][C]38.57[/C][C]38.2638105690919[/C][C]0.306189430908143[/C][/ROW]
[ROW][C]244[/C][C]37.84[/C][C]37.8758200903928[/C][C]-0.0358200903927714[/C][/ROW]
[ROW][C]245[/C][C]37.36[/C][C]37.3408842544609[/C][C]0.0191157455390873[/C][/ROW]
[ROW][C]246[/C][C]37.08[/C][C]37.657019621127[/C][C]-0.577019621127017[/C][/ROW]
[ROW][C]247[/C][C]36.45[/C][C]36.6675715751736[/C][C]-0.217571575173601[/C][/ROW]
[ROW][C]248[/C][C]37.02[/C][C]36.545931877985[/C][C]0.474068122014966[/C][/ROW]
[ROW][C]249[/C][C]37.68[/C][C]36.7975535071285[/C][C]0.882446492871483[/C][/ROW]
[ROW][C]250[/C][C]37.67[/C][C]36.4445993586432[/C][C]1.2254006413568[/C][/ROW]
[ROW][C]251[/C][C]38.55[/C][C]37.5759636553129[/C][C]0.974036344687142[/C][/ROW]
[ROW][C]252[/C][C]38.16[/C][C]37.6235814728451[/C][C]0.536418527154871[/C][/ROW]
[ROW][C]253[/C][C]38.96[/C][C]38.5265964310868[/C][C]0.433403568913243[/C][/ROW]
[ROW][C]254[/C][C]38.05[/C][C]37.7483052288382[/C][C]0.301694771161758[/C][/ROW]
[ROW][C]255[/C][C]38.77[/C][C]38.5869600102069[/C][C]0.183039989793133[/C][/ROW]
[ROW][C]256[/C][C]38.76[/C][C]38.5706278931745[/C][C]0.189372106825531[/C][/ROW]
[ROW][C]257[/C][C]38.86[/C][C]38.7284084311611[/C][C]0.131591568838847[/C][/ROW]
[ROW][C]258[/C][C]38.49[/C][C]38.3220031477918[/C][C]0.167996852208212[/C][/ROW]
[ROW][C]259[/C][C]38.29[/C][C]37.9398776101698[/C][C]0.350122389830249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
138.5839.7689232306809-1.1889232306809
238.4839.6740242249035-1.19402422490347
338.5639.8128386134993-1.2528386134993
438.2539.1081196102394-0.858119610239446
537.9738.8783360006117-0.90833600061169
638.4238.9119332028039-0.491933202803883
738.639.3100019543366-0.710001954336552
838.339.0128074330144-0.712807433014432
938.2238.797295864792-0.577295864792031
1038.2238.5243480396675-0.304348039667498
1138.2238.3422642330419-0.122264233041943
1236.9837.2085435185907-0.22854351859069
1337.4337.8188197610727-0.388819761072668
1437.5237.8749669781264-0.354966978126353
1537.9838.1868833988012-0.206883398801212
1637.8337.8491348185152-0.0191348185152236
173838.0838785250013-0.0838785250012611
1837.737.8028170905511-0.10281709055111
1937.8837.86734542226540.0126545777346172
2039.0238.71252952844650.307470471553539
2138.8438.37568904396850.464310956031463
2239.4438.74332101309530.696678986904709
2339.1238.52813659687260.591863403127417
2438.8238.38360697302940.436393026970576
2538.9938.47264562755840.517354372441637
2638.3937.77837978674610.611620213253877
2738.7138.09396184281070.61603815718931
2838.4338.04743995844190.38256004155805
2938.6738.18020818896650.489791811033509
3038.4537.94991790608870.5000820939113
3139.3438.80077723010490.539222769895091
3239.639.09413521731440.505864782685603
3339.8439.47308993378890.366910066211128
344039.36833407877820.631665921221825
3539.5539.02815370290060.521846297099411
3638.538.20803278549170.291967214508322
3738.1338.0832130070230.0467869929769685
3838.7538.4121915806830.337808419316968
3938.237.94104124278430.258958757215679
4038.3938.34106587093670.0489341290633026
4138.2938.6322798492007-0.342279849200658
4238.7339.2582565035172-0.528256503517192
4338.3338.6107339885989-0.280733988598858
4438.7338.5890982697870.140901730212967
4539.0638.73848458023240.321515419767622
4639.2839.07173806872360.208261931276415
4738.638.06367875675520.536321243244774
4839.6839.06204558897330.617954411026714
4939.6138.60001985637591.00998014362407
5040.7439.68674094331241.05325905668763
5140.5539.53470128967831.01529871032175
5240.840.03800422268220.761995777317837
5340.8139.48043957460061.32956042539938
5441.4740.05491695166031.41508304833973
554139.92818597898121.07181402101878
5641.4240.32393519231441.09606480768565
5741.8440.69037218367671.14962781632335
5840.8939.82868629883821.06131370116179
5941.0540.108864492420.941135507579984
6041.240.07906597631961.12093402368041
6140.4539.82024388872960.629756111270386
6240.5540.07373527146130.476264728538675
6340.539.995102099090.504897900909978
6439.2338.79046936243470.439530637565318
6539.4238.61935439497490.800645605025125
6640.0539.5829442009490.46705579905099
6739.739.2941192110030.405880788997007
6839.1739.15008141939080.0199185806091803
6939.4239.5244170520893-0.104417052089279
7039.2439.6438390209411-0.403839020941104
7139.639.9125060778597-0.312506077859726
7239.3839.559560105952-0.179560105951991
7339.3839.5136436711806-0.133643671180594
7439.839.8441483517715-0.044148351771462
7540.4540.4529174580921-0.00291745809204928
7640.4539.93646284690240.513537153097642
7740.3840.13169143998730.248308560012666
7840.2540.0338985091850.216101490814956
7940.0339.83989901963640.190100980363595
804039.78179310131030.218206898689692
8139.7639.54820863336740.211791366632625
8239.9639.47356690544950.486433094550538
834039.7582189514560.241781048544014
8439.939.6210673599610.278932640039034
8539.7639.7701716166258-0.0101716166258026
8638.939.3185003097135-0.418500309713472
8738.9238.9532840218379-0.0332840218379352
8837.3437.3850308578525-0.0450308578524933
8937.9938.5113689252805-0.521368925280479
9037.638.1438701789659-0.543870178965909
9137.4538.3984853121434-0.948485312143427
9237.3537.9667549418992-0.616754941899248
9336.1237.1438626987019-1.02386269870194
9434.8335.7025371145849-0.872537114584893
9534.8335.5694829177191-0.739482917719087
9635.3935.7294974182283-0.339497418228288
9736.0536.7238034868144-0.673803486814436
9836.6637.5578301153064-0.897830115306391
9936.5437.3116320497128-0.771632049712795
10035.8736.674548765642-0.804548765641962
10136.0136.6669933665758-0.656993366575791
10236.0336.6749138257867-0.64491382578667
10335.6336.0148548636681-0.384854863668123
10436.0436.1990657721949-0.159065772194856
10535.9636.4339953251341-0.473995325134131
10635.9435.87575323776080.0642467622392011
10736.0636.1073386921403-0.0473386921402804
10836.5236.6962936492218-0.176293649221777
10936.9137.3051701457328-0.395170145732774
11037.0537.3922836881575-0.342283688157542
11135.9837.0638027546069-1.08380275460693
11235.536.4827433849168-0.982743384916835
11334.0434.8161374673555-0.776137467355515
11434.234.8719404231151-0.67194042311508
11533.6334.3048608490162-0.67486084901619
11633.8434.725170743531-0.885170743530978
11734.4135.5468675815005-1.13686758150053
11834.8435.9001527786768-1.06015277867676
11935.235.8361194220965-0.636119422096541
12035.335.6356126590107-0.335612659010687
12134.834.9943160006428-0.194316000642804
12235.4335.13298977738840.297010222611607
12334.8834.52096158058950.359038419410526
12434.8134.34928041617180.460719583828167
12534.8334.57210410464150.257895895358521
12634.734.34268664932170.357313350678259
12734.5934.57560629151580.0143937084842081
12834.7734.69270805381830.0772919461816568
12934.834.52518851488590.274811485114105
13034.3233.98046734863210.339532651367886
13133.9633.62313410812390.336865891876087
1323433.66825501015450.331744989845513
13334.7734.03392467789190.736075322108057
13434.5334.11167100288030.418328997119685
13535.234.93596105174780.264038948252174
13635.0633.86168711846281.19831288153717
13735.1834.11581752539671.06418247460334
1383533.93192424986921.06807575013081
13934.4933.48848095141411.00151904858595
14035.1534.45713195388820.692868046111829
14134.5933.83207109271020.757928907289817
14234.6533.45000640290691.19999359709308
14334.5933.7595100533110.830489946689001
14434.9234.5130845325890.406915467410981
14534.3734.35623951976830.0137604802316702
14634.4734.7717115615989-0.301711561598928
14735.1335.482737474481-0.352737474480963
14835.1535.5214586015715-0.371458601571488
14934.4835.2481969279837-0.768196927983733
15034.9135.3769928468341-0.466992846834115
15135.9536.2562809409727-0.306280940972645
15235.5236.175612793105-0.655612793105005
15336.1636.6846138928611-0.524613892861061
15436.1536.6681928079624-0.51819280796245
15536.0736.6755336383239-0.605533638323942
15636.537.1541712797169-0.654171279716886
15736.5136.7584070950347-0.24840709503466
15836.2336.6468224727105-0.416822472710491
15935.9136.0175523761325-0.107552376132465
16035.5635.53702843480110.0229715651988746
16136.4536.6800696561892-0.230069656189159
16236.3436.8379268328557-0.497926832855706
16337.3237.626304836063-0.306304836062998
16437.4738.2319303724758-0.761930372475837
16536.9837.2151580264646-0.235158026464654
16636.4237.0504493964686-0.630449396468581
16737.0437.9094629947669-0.8694629947669
16837.1537.7007904879194-0.550790487919393
16937.1337.6312846835723-0.501284683572261
17038.2138.6086616277641-0.3986616277641
17137.9138.5360537688835-0.626053768883503
17238.439.6752588656356-1.27525886563556
17339.1240.4065015164438-1.28650151644382
17438.0540.0493817555957-1.99938175559569
17537.8339.6260432413294-1.79604324132939
17638.0240.3010174192673-2.28101741926731
17738.4340.7811334509192-2.35113345091924
17840.9441.1966133751042-0.256613375104173
17940.7540.9452372807163-0.195237280716296
18041.0640.97436130479060.085638695209399
18141.6941.7030372111097-0.0130372111097065
18241.7341.53563111203530.194368887964668
18342.3442.29273715038030.0472628496197313
18442.5442.8394913926692-0.299491392669207
18542.542.93775253839-0.437752538389977
18642.7842.8477283497125-0.0677283497125115
18742.6542.61810590394210.0318940960579113
1884241.95227133330770.0477286666922579
18942.341.9341088235910.365891176409037
19042.0241.77517545221280.244824547787174
19141.5240.77912324221560.740876757784428
19241.7740.40967306888091.36032693111909
19342.4341.88480111111050.545198888889499
19442.4342.06346131969550.366538680304508
19542.4841.96146772344420.518532276555823
19642.0141.45519886932330.554801130676717
19741.9941.60479157906740.385208420932651
19842.0141.38525245018490.624747549815137
19942.0541.68419178913750.36580821086249
20041.8441.49902112082460.340978879175403
20141.7941.57964863208350.21035136791648
20241.8241.65797584951840.162024150481613
20341.8741.62243684695290.247563153047142
20441.6641.42931325782880.230686742171239
20541.1940.90017764958470.28982235041528
20640.9940.993857495366-0.00385749536600836
20741.1540.73984664396120.410153356038757
20840.9541.0440301216364-0.0940301216363869
20940.6741.0008904103083-0.330890410308265
21041.141.4330834210091-0.333083421009131
21140.8841.2305999202436-0.350599920243619
21240.9341.2699824006978-0.339982400697815
21340.8941.4136167023239-0.523616702323936
21440.9741.7940040949736-0.824004094973604
21540.8741.2529563282092-0.382956328209159
21640.5641.1154498933449-0.555449893344855
21740.4740.3592124479340.110787552066026
21840.0139.87017302332520.139826976674762
21940.2340.5848916130254-0.354891613025404
22040.4541.0273376029699-0.577337602969928
22140.340.6533923731907-0.353392373190656
22240.3840.7724920381345-0.392492038134522
22339.9540.9175618847197-0.967561884719713
22439.7440.52544494108-0.78544494108004
22540.3740.677385296735-0.307385296735008
22640.0540.0812853036733-0.0312853036733374
22740.1440.11590057501230.0240994249877138
22839.4239.654896564177-0.234896564177019
22938.9739.388419383664-0.418419383664045
23039.0639.3898655751324-0.329865575132395
23139.8639.36509677211080.494903227889226
23240.4939.30117671637431.18882328362575
23339.9938.77711577168371.21288422831627
23439.9438.66546452243211.27453547756793
23539.9738.74186974827511.22813025172486
23640.2139.52654605180680.683453948193185
23740.3939.90167935035220.488320649647805
23839.9539.58959587506930.360404124930749
23939.4639.03534011307670.424659886923292
24039.0738.84688155236470.22311844763525
24138.6438.22989977094150.410100229058537
24238.9638.4884858454390.471514154560983
24338.5738.26381056909190.306189430908143
24437.8437.8758200903928-0.0358200903927714
24537.3637.34088425446090.0191157455390873
24637.0837.657019621127-0.577019621127017
24736.4536.6675715751736-0.217571575173601
24837.0236.5459318779850.474068122014966
24937.6836.79755350712850.882446492871483
25037.6736.44459935864321.2254006413568
25138.5537.57596365531290.974036344687142
25238.1637.62358147284510.536418527154871
25338.9638.52659643108680.433403568913243
25438.0537.74830522883820.301694771161758
25538.7738.58696001020690.183039989793133
25638.7638.57062789317450.189372106825531
25738.8638.72840843116110.131591568838847
25838.4938.32200314779180.167996852208212
25938.2937.93987761016980.350122389830249






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.009684964734316890.01936992946863380.990315035265683
90.004375646244370960.008751292488741910.995624353755629
100.0008266838808222090.001653367761644420.999173316119178
110.0001717665388587180.0003435330777174360.999828233461141
120.000196719946644590.0003934398932891790.999803280053355
136.13833656487746e-050.0001227667312975490.999938616634351
141.39904755356717e-052.79809510713435e-050.999986009524464
152.8310251682316e-065.6620503364632e-060.999997168974832
165.67942284191735e-071.13588456838347e-060.999999432057716
171.0651064453446e-072.1302128906892e-070.999999893489355
182.53461703098142e-085.06923406196283e-080.99999997465383
194.9489027405535e-099.897805481107e-090.999999995051097
204.66418284070114e-099.32836568140227e-090.999999995335817
219.12204117025081e-101.82440823405016e-090.999999999087796
228.45627440261475e-101.69125488052295e-090.999999999154373
231.64397482728504e-103.28794965457008e-100.999999999835603
243.82309332112984e-117.64618664225967e-110.999999999961769
251.10219876858871e-112.20439753717742e-110.999999999988978
262.36749356569905e-124.7349871313981e-120.999999999997633
274.78178498836949e-139.56356997673897e-130.999999999999522
283.3006795113064e-136.6013590226128e-130.99999999999967
291.86088414002388e-123.72176828004776e-120.999999999998139
302.63636783467993e-115.27273566935986e-110.999999999973636
316.75434933238049e-111.3508698664761e-100.999999999932456
323.82971453059472e-117.65942906118943e-110.999999999961703
332.92004503376198e-115.84009006752396e-110.9999999999708
348.26741201321174e-121.65348240264235e-110.999999999991733
354.52400485469285e-129.04800970938571e-120.999999999995476
361.24711795023875e-112.49423590047751e-110.999999999987529
375.84104941971563e-121.16820988394313e-110.999999999994159
383.22574136722902e-126.45148273445803e-120.999999999996774
399.93992712855076e-131.98798542571015e-120.999999999999006
403.17738622694051e-136.35477245388103e-130.999999999999682
412.71315313083135e-135.42630626166269e-130.999999999999729
422.04977373985681e-134.09954747971362e-130.999999999999795
431.10688853278645e-132.21377706557289e-130.999999999999889
443.45083371196925e-146.9016674239385e-140.999999999999965
451.67892552487513e-143.35785104975025e-140.999999999999983
467.14939088927257e-151.42987817785451e-140.999999999999993
472.50761896438244e-155.01523792876488e-150.999999999999997
484.17500695576183e-158.35001391152365e-150.999999999999996
496.85102817111432e-151.37020563422286e-140.999999999999993
501.66151249597993e-143.32302499195986e-140.999999999999983
511.72008770346535e-143.4401754069307e-140.999999999999983
521.49745628861167e-142.99491257722333e-140.999999999999985
531.70161699170938e-143.40323398341877e-140.999999999999983
541.1516827847658e-122.3033655695316e-120.999999999998848
551.92313976482815e-123.84627952965631e-120.999999999998077
561.55641139503275e-123.11282279006551e-120.999999999998444
571.59799663408246e-123.19599326816493e-120.999999999998402
581.35556255876958e-122.71112511753915e-120.999999999998644
592.26192006423308e-124.52384012846617e-120.999999999997738
602.26036148413248e-124.52072296826495e-120.99999999999774
613.70640577571662e-127.41281155143323e-120.999999999996294
626.52957379565497e-121.30591475913099e-110.99999999999347
638.86721735679859e-121.77344347135972e-110.999999999991133
641.28596806460455e-112.57193612920911e-110.99999999998714
658.69548501519817e-121.73909700303963e-110.999999999991305
664.64304740615254e-129.28609481230508e-120.999999999995357
672.88143466772282e-125.76286933544564e-120.999999999997119
681.26512485793485e-122.53024971586969e-120.999999999998735
696.95430587554209e-131.39086117510842e-120.999999999999305
703.04422116606028e-126.08844233212056e-120.999999999996956
712.71726804848503e-115.43453609697006e-110.999999999972827
726.47848463199081e-111.29569692639816e-100.999999999935215
732.24508492974733e-104.49016985949467e-100.999999999775491
744.42886551163408e-108.85773102326817e-100.999999999557113
759.12847896249464e-101.82569579249893e-090.999999999087152
761.06243893529058e-092.12487787058115e-090.999999998937561
771.5064368539811e-093.0128737079622e-090.999999998493563
783.85366466776972e-097.70732933553944e-090.999999996146335
794.36441414368529e-098.72882828737058e-090.999999995635586
806.55516201956571e-091.31103240391314e-080.999999993444838
819.11628180600799e-091.8232563612016e-080.999999990883718
822.2145406104161e-084.4290812208322e-080.999999977854594
836.58281492345454e-081.31656298469091e-070.999999934171851
848.26214264010691e-081.65242852802138e-070.999999917378574
853.34408593613617e-076.68817187227234e-070.999999665591406
862.16499908918572e-064.32999817837143e-060.999997835000911
874.5750877556312e-069.1501755112624e-060.999995424912244
887.10701371256759e-061.42140274251352e-050.999992892986287
891.75233422674932e-053.50466845349863e-050.999982476657733
904.16996301062127e-058.33992602124255e-050.999958300369894
910.0003993548052387390.0007987096104774780.999600645194761
920.0007053635397815080.001410727079563020.999294636460219
930.001507371349266010.003014742698532020.998492628650734
940.001403347520761240.002806695041522480.998596652479239
950.001194599996910210.002389199993820420.99880540000309
960.0009488593066994910.001897718613398980.9990511406933
970.001768773127453230.003537546254906460.998231226872547
980.005577305197248370.01115461039449670.994422694802752
990.008598002906695330.01719600581339070.991401997093305
1000.00905538774613960.01811077549227920.99094461225386
1010.008567729858447480.0171354597168950.991432270141553
1020.007954094890492320.01590818978098460.992045905109508
1030.006412404388531040.01282480877706210.993587595611469
1040.005291738153903440.01058347630780690.994708261846097
1050.005038048655157290.01007609731031460.994961951344843
1060.005207615860614640.01041523172122930.994792384139385
1070.004855014878261840.009710029756523680.995144985121738
1080.006290716535920860.01258143307184170.993709283464079
1090.008603249045710470.01720649809142090.99139675095429
1100.01010897958607330.02021795917214660.989891020413927
1110.02084103230440570.04168206460881130.979158967695594
1120.02744366980480330.05488733960960660.972556330195197
1130.0230955435174260.04619108703485190.976904456482574
1140.01948646882605350.03897293765210710.980513531173946
1150.01672051378679270.03344102757358550.983279486213207
1160.01587646523455230.03175293046910470.984123534765448
1170.01903866497132570.03807732994265140.980961335028674
1180.02250623378557320.04501246757114640.977493766214427
1190.02031239516568720.04062479033137440.979687604834313
1200.01728488313729670.03456976627459340.982715116862703
1210.015450167034920.030900334069840.98454983296508
1220.01577027136667510.03154054273335020.984229728633325
1230.01821711240710510.03643422481421020.981782887592895
1240.02057250069695740.04114500139391470.979427499303043
1250.01856784284446290.03713568568892580.981432157155537
1260.01650756724261460.03301513448522910.983492432757385
1270.0131557083952870.0263114167905740.986844291604713
1280.01040366704500590.02080733409001180.989596332954994
1290.008406013770918570.01681202754183710.991593986229081
1300.008883280151461530.01776656030292310.991116719848538
1310.009802922598797230.01960584519759450.990197077401203
1320.01074903776107880.02149807552215760.989250962238921
1330.01103549878914740.02207099757829470.988964501210853
1340.009092645004814550.01818529000962910.990907354995185
1350.007227829683162580.01445565936632520.992772170316837
1360.01038992530197320.02077985060394650.989610074698027
1370.01330026488457750.0266005297691550.986699735115423
1380.01851079358035090.03702158716070190.981489206419649
1390.02151853104134960.04303706208269920.97848146895865
1400.02165708417250440.04331416834500880.978342915827496
1410.02142945838151750.0428589167630350.978570541618483
1420.03144193292414150.06288386584828310.968558067075858
1430.03806671859034420.07613343718068830.961933281409656
1440.03581708427589630.07163416855179260.964182915724104
1450.03477324091614570.06954648183229150.965226759083854
1460.03667989641478610.07335979282957220.963320103585214
1470.05180684952343240.1036136990468650.948193150476568
1480.06709389237797520.134187784755950.932906107622025
1490.1147896779466760.2295793558933510.885210322053324
1500.1373595382725750.274719076545150.862640461727425
1510.1776506121405350.3553012242810690.822349387859465
1520.1903802286970360.3807604573940730.809619771302964
1530.2103228319266880.4206456638533750.789677168073312
1540.2256474104832390.4512948209664780.774352589516761
1550.2288179866019350.457635973203870.771182013398065
1560.2521391279932480.5042782559864960.747860872006752
1570.2417646321991430.4835292643982860.758235367800857
1580.2369378455722310.4738756911444610.763062154427769
1590.2293763822395570.4587527644791130.770623617760443
1600.2258965183275420.4517930366550840.774103481672458
1610.2124614937126590.4249229874253170.787538506287341
1620.1902183848279260.3804367696558520.809781615172074
1630.1761068930421670.3522137860843340.823893106957833
1640.1640607872124330.3281215744248650.835939212787567
1650.1560477141468240.3120954282936480.843952285853176
1660.1386792160951310.2773584321902630.861320783904869
1670.1288690225581780.2577380451163560.871130977441822
1680.1154491380937110.2308982761874210.884550861906289
1690.1034220632803850.206844126560770.896577936719615
1700.09583691584063390.1916738316812680.904163084159366
1710.08778002000588850.1755600400117770.912219979994112
1720.1103698288983240.2207396577966490.889630171101676
1730.1199447829525180.2398895659050360.880055217047482
1740.2026506960049530.4053013920099060.797349303995047
1750.3370156423136030.6740312846272050.662984357686397
1760.7811635068160940.4376729863678110.218836493183906
1770.9966309564821290.006738087035741510.00336904351787076
1780.9974728964645380.005054207070924580.00252710353546229
1790.9984615909574080.003076818085184530.00153840904259226
1800.9989090651792980.002181869641403860.00109093482070193
1810.9990794012545030.001841197490993530.000920598745496765
1820.9992190282930350.001561943413930020.000780971706965009
1830.9991881452235990.001623709552801910.000811854776400954
1840.9992165486813430.001566902637314040.00078345131865702
1850.9993270981174190.001345803765161290.000672901882580645
1860.9991837908816780.001632418236644160.000816209118322081
1870.9990363951170360.001927209765927180.000963604882963588
1880.9990552856280810.001889428743838430.000944714371919215
1890.9989899479597120.002020104080576480.00101005204028824
1900.9989313221914540.00213735561709230.00106867780854615
1910.999058542068370.001882915863260280.000941457931630141
1920.9996006152810550.0007987694378894790.00039938471894474
1930.9995280703727050.0009438592545902980.000471929627295149
1940.9993777434528790.001244513094242260.000622256547121129
1950.9992376850021150.001524629995770450.000762314997885227
1960.9990623613468090.001875277306382090.000937638653191047
1970.9987421516748090.002515696650382950.00125784832519148
1980.9985154639935590.002969072012881320.00148453600644066
1990.9983195760774420.003360847845115140.00168042392255757
2000.9981599224463280.00368015510734440.0018400775536722
2010.9977175505905450.004564898818910870.00228244940945543
2020.9970198196667340.005960360666532220.00298018033326611
2030.996613147506170.006773704987660630.00338685249383032
2040.9964448563485440.007110287302912320.00355514365145616
2050.9962358817680290.007528236463942010.003764118231971
2060.9951055512151690.00978889756966120.0048944487848306
2070.9959710796069050.008057840786190040.00402892039309502
2080.9947539989541940.01049200209161220.0052460010458061
2090.9925774304189970.01484513916200570.00742256958100283
2100.989820982463520.02035803507296090.0101790175364804
2110.986052841870910.02789431625818080.0139471581290904
2120.9812934899286590.03741302014268220.0187065100713411
2130.9746270656201280.0507458687597440.025372934379872
2140.9690502066953860.06189958660922710.0309497933046135
2150.9588065994607140.0823868010785720.041193400539286
2160.9480173779846560.1039652440306880.0519826220153442
2170.9378339200405690.1243321599188630.0621660799594313
2180.9258011246690330.1483977506619340.0741988753309672
2190.9057126015000550.1885747969998910.0942873984999454
2200.886722845592890.2265543088142210.11327715440711
2210.8624501425750130.2750997148499740.137549857424987
2220.8357542395972940.3284915208054120.164245760402706
2230.8702946499388420.2594107001223150.129705350061158
2240.9184450922781460.1631098154437090.0815549077218545
2250.9191971953528590.1616056092942820.0808028046471408
2260.9072373693256590.1855252613486810.0927626306743405
2270.8966345048751540.2067309902496930.103365495124847
2280.9217771199719640.1564457600560710.0782228800280356
2290.9676635692230290.06467286155394230.0323364307769712
2300.9968867558036290.006226488392742550.00311324419637127
2310.9989266909506860.002146618098627150.00107330904931357
2320.9987288870900190.002542225819962230.00127111290998112
2330.9981284041715380.003743191656923490.00187159582846175
2340.9974015274055060.005196945188987360.00259847259449368
2350.9966071886519960.006785622696007250.00339281134800363
2360.9948991827562020.01020163448759620.00510081724379809
2370.9912380740919040.01752385181619210.00876192590809606
2380.9851445100730140.02971097985397290.0148554899269865
2390.9765811500182340.04683769996353230.0234188499817662
2400.9640895014356940.07182099712861260.0359104985643063
2410.9639842706918330.07203145861633390.0360157293081669
2420.9963095068043990.007380986391201790.00369049319560089
2430.998130381691680.003739236616639560.00186961830831978
2440.9986015403543270.002796919291346570.00139845964567329
2450.9964208836847760.007158232630448820.00357911631522441
2460.9911378141361950.01772437172760980.00886218586380491
2470.9991346544089670.001730691182066790.000865345591033395
2480.999819813827410.0003603723451793750.000180186172589688
2490.9993824543204310.0012350913591370.0006175456795685
2500.9971012260351630.005797547929672940.00289877396483647
2510.9957954849227590.008409030154482030.00420451507724102

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.00968496473431689 & 0.0193699294686338 & 0.990315035265683 \tabularnewline
9 & 0.00437564624437096 & 0.00875129248874191 & 0.995624353755629 \tabularnewline
10 & 0.000826683880822209 & 0.00165336776164442 & 0.999173316119178 \tabularnewline
11 & 0.000171766538858718 & 0.000343533077717436 & 0.999828233461141 \tabularnewline
12 & 0.00019671994664459 & 0.000393439893289179 & 0.999803280053355 \tabularnewline
13 & 6.13833656487746e-05 & 0.000122766731297549 & 0.999938616634351 \tabularnewline
14 & 1.39904755356717e-05 & 2.79809510713435e-05 & 0.999986009524464 \tabularnewline
15 & 2.8310251682316e-06 & 5.6620503364632e-06 & 0.999997168974832 \tabularnewline
16 & 5.67942284191735e-07 & 1.13588456838347e-06 & 0.999999432057716 \tabularnewline
17 & 1.0651064453446e-07 & 2.1302128906892e-07 & 0.999999893489355 \tabularnewline
18 & 2.53461703098142e-08 & 5.06923406196283e-08 & 0.99999997465383 \tabularnewline
19 & 4.9489027405535e-09 & 9.897805481107e-09 & 0.999999995051097 \tabularnewline
20 & 4.66418284070114e-09 & 9.32836568140227e-09 & 0.999999995335817 \tabularnewline
21 & 9.12204117025081e-10 & 1.82440823405016e-09 & 0.999999999087796 \tabularnewline
22 & 8.45627440261475e-10 & 1.69125488052295e-09 & 0.999999999154373 \tabularnewline
23 & 1.64397482728504e-10 & 3.28794965457008e-10 & 0.999999999835603 \tabularnewline
24 & 3.82309332112984e-11 & 7.64618664225967e-11 & 0.999999999961769 \tabularnewline
25 & 1.10219876858871e-11 & 2.20439753717742e-11 & 0.999999999988978 \tabularnewline
26 & 2.36749356569905e-12 & 4.7349871313981e-12 & 0.999999999997633 \tabularnewline
27 & 4.78178498836949e-13 & 9.56356997673897e-13 & 0.999999999999522 \tabularnewline
28 & 3.3006795113064e-13 & 6.6013590226128e-13 & 0.99999999999967 \tabularnewline
29 & 1.86088414002388e-12 & 3.72176828004776e-12 & 0.999999999998139 \tabularnewline
30 & 2.63636783467993e-11 & 5.27273566935986e-11 & 0.999999999973636 \tabularnewline
31 & 6.75434933238049e-11 & 1.3508698664761e-10 & 0.999999999932456 \tabularnewline
32 & 3.82971453059472e-11 & 7.65942906118943e-11 & 0.999999999961703 \tabularnewline
33 & 2.92004503376198e-11 & 5.84009006752396e-11 & 0.9999999999708 \tabularnewline
34 & 8.26741201321174e-12 & 1.65348240264235e-11 & 0.999999999991733 \tabularnewline
35 & 4.52400485469285e-12 & 9.04800970938571e-12 & 0.999999999995476 \tabularnewline
36 & 1.24711795023875e-11 & 2.49423590047751e-11 & 0.999999999987529 \tabularnewline
37 & 5.84104941971563e-12 & 1.16820988394313e-11 & 0.999999999994159 \tabularnewline
38 & 3.22574136722902e-12 & 6.45148273445803e-12 & 0.999999999996774 \tabularnewline
39 & 9.93992712855076e-13 & 1.98798542571015e-12 & 0.999999999999006 \tabularnewline
40 & 3.17738622694051e-13 & 6.35477245388103e-13 & 0.999999999999682 \tabularnewline
41 & 2.71315313083135e-13 & 5.42630626166269e-13 & 0.999999999999729 \tabularnewline
42 & 2.04977373985681e-13 & 4.09954747971362e-13 & 0.999999999999795 \tabularnewline
43 & 1.10688853278645e-13 & 2.21377706557289e-13 & 0.999999999999889 \tabularnewline
44 & 3.45083371196925e-14 & 6.9016674239385e-14 & 0.999999999999965 \tabularnewline
45 & 1.67892552487513e-14 & 3.35785104975025e-14 & 0.999999999999983 \tabularnewline
46 & 7.14939088927257e-15 & 1.42987817785451e-14 & 0.999999999999993 \tabularnewline
47 & 2.50761896438244e-15 & 5.01523792876488e-15 & 0.999999999999997 \tabularnewline
48 & 4.17500695576183e-15 & 8.35001391152365e-15 & 0.999999999999996 \tabularnewline
49 & 6.85102817111432e-15 & 1.37020563422286e-14 & 0.999999999999993 \tabularnewline
50 & 1.66151249597993e-14 & 3.32302499195986e-14 & 0.999999999999983 \tabularnewline
51 & 1.72008770346535e-14 & 3.4401754069307e-14 & 0.999999999999983 \tabularnewline
52 & 1.49745628861167e-14 & 2.99491257722333e-14 & 0.999999999999985 \tabularnewline
53 & 1.70161699170938e-14 & 3.40323398341877e-14 & 0.999999999999983 \tabularnewline
54 & 1.1516827847658e-12 & 2.3033655695316e-12 & 0.999999999998848 \tabularnewline
55 & 1.92313976482815e-12 & 3.84627952965631e-12 & 0.999999999998077 \tabularnewline
56 & 1.55641139503275e-12 & 3.11282279006551e-12 & 0.999999999998444 \tabularnewline
57 & 1.59799663408246e-12 & 3.19599326816493e-12 & 0.999999999998402 \tabularnewline
58 & 1.35556255876958e-12 & 2.71112511753915e-12 & 0.999999999998644 \tabularnewline
59 & 2.26192006423308e-12 & 4.52384012846617e-12 & 0.999999999997738 \tabularnewline
60 & 2.26036148413248e-12 & 4.52072296826495e-12 & 0.99999999999774 \tabularnewline
61 & 3.70640577571662e-12 & 7.41281155143323e-12 & 0.999999999996294 \tabularnewline
62 & 6.52957379565497e-12 & 1.30591475913099e-11 & 0.99999999999347 \tabularnewline
63 & 8.86721735679859e-12 & 1.77344347135972e-11 & 0.999999999991133 \tabularnewline
64 & 1.28596806460455e-11 & 2.57193612920911e-11 & 0.99999999998714 \tabularnewline
65 & 8.69548501519817e-12 & 1.73909700303963e-11 & 0.999999999991305 \tabularnewline
66 & 4.64304740615254e-12 & 9.28609481230508e-12 & 0.999999999995357 \tabularnewline
67 & 2.88143466772282e-12 & 5.76286933544564e-12 & 0.999999999997119 \tabularnewline
68 & 1.26512485793485e-12 & 2.53024971586969e-12 & 0.999999999998735 \tabularnewline
69 & 6.95430587554209e-13 & 1.39086117510842e-12 & 0.999999999999305 \tabularnewline
70 & 3.04422116606028e-12 & 6.08844233212056e-12 & 0.999999999996956 \tabularnewline
71 & 2.71726804848503e-11 & 5.43453609697006e-11 & 0.999999999972827 \tabularnewline
72 & 6.47848463199081e-11 & 1.29569692639816e-10 & 0.999999999935215 \tabularnewline
73 & 2.24508492974733e-10 & 4.49016985949467e-10 & 0.999999999775491 \tabularnewline
74 & 4.42886551163408e-10 & 8.85773102326817e-10 & 0.999999999557113 \tabularnewline
75 & 9.12847896249464e-10 & 1.82569579249893e-09 & 0.999999999087152 \tabularnewline
76 & 1.06243893529058e-09 & 2.12487787058115e-09 & 0.999999998937561 \tabularnewline
77 & 1.5064368539811e-09 & 3.0128737079622e-09 & 0.999999998493563 \tabularnewline
78 & 3.85366466776972e-09 & 7.70732933553944e-09 & 0.999999996146335 \tabularnewline
79 & 4.36441414368529e-09 & 8.72882828737058e-09 & 0.999999995635586 \tabularnewline
80 & 6.55516201956571e-09 & 1.31103240391314e-08 & 0.999999993444838 \tabularnewline
81 & 9.11628180600799e-09 & 1.8232563612016e-08 & 0.999999990883718 \tabularnewline
82 & 2.2145406104161e-08 & 4.4290812208322e-08 & 0.999999977854594 \tabularnewline
83 & 6.58281492345454e-08 & 1.31656298469091e-07 & 0.999999934171851 \tabularnewline
84 & 8.26214264010691e-08 & 1.65242852802138e-07 & 0.999999917378574 \tabularnewline
85 & 3.34408593613617e-07 & 6.68817187227234e-07 & 0.999999665591406 \tabularnewline
86 & 2.16499908918572e-06 & 4.32999817837143e-06 & 0.999997835000911 \tabularnewline
87 & 4.5750877556312e-06 & 9.1501755112624e-06 & 0.999995424912244 \tabularnewline
88 & 7.10701371256759e-06 & 1.42140274251352e-05 & 0.999992892986287 \tabularnewline
89 & 1.75233422674932e-05 & 3.50466845349863e-05 & 0.999982476657733 \tabularnewline
90 & 4.16996301062127e-05 & 8.33992602124255e-05 & 0.999958300369894 \tabularnewline
91 & 0.000399354805238739 & 0.000798709610477478 & 0.999600645194761 \tabularnewline
92 & 0.000705363539781508 & 0.00141072707956302 & 0.999294636460219 \tabularnewline
93 & 0.00150737134926601 & 0.00301474269853202 & 0.998492628650734 \tabularnewline
94 & 0.00140334752076124 & 0.00280669504152248 & 0.998596652479239 \tabularnewline
95 & 0.00119459999691021 & 0.00238919999382042 & 0.99880540000309 \tabularnewline
96 & 0.000948859306699491 & 0.00189771861339898 & 0.9990511406933 \tabularnewline
97 & 0.00176877312745323 & 0.00353754625490646 & 0.998231226872547 \tabularnewline
98 & 0.00557730519724837 & 0.0111546103944967 & 0.994422694802752 \tabularnewline
99 & 0.00859800290669533 & 0.0171960058133907 & 0.991401997093305 \tabularnewline
100 & 0.0090553877461396 & 0.0181107754922792 & 0.99094461225386 \tabularnewline
101 & 0.00856772985844748 & 0.017135459716895 & 0.991432270141553 \tabularnewline
102 & 0.00795409489049232 & 0.0159081897809846 & 0.992045905109508 \tabularnewline
103 & 0.00641240438853104 & 0.0128248087770621 & 0.993587595611469 \tabularnewline
104 & 0.00529173815390344 & 0.0105834763078069 & 0.994708261846097 \tabularnewline
105 & 0.00503804865515729 & 0.0100760973103146 & 0.994961951344843 \tabularnewline
106 & 0.00520761586061464 & 0.0104152317212293 & 0.994792384139385 \tabularnewline
107 & 0.00485501487826184 & 0.00971002975652368 & 0.995144985121738 \tabularnewline
108 & 0.00629071653592086 & 0.0125814330718417 & 0.993709283464079 \tabularnewline
109 & 0.00860324904571047 & 0.0172064980914209 & 0.99139675095429 \tabularnewline
110 & 0.0101089795860733 & 0.0202179591721466 & 0.989891020413927 \tabularnewline
111 & 0.0208410323044057 & 0.0416820646088113 & 0.979158967695594 \tabularnewline
112 & 0.0274436698048033 & 0.0548873396096066 & 0.972556330195197 \tabularnewline
113 & 0.023095543517426 & 0.0461910870348519 & 0.976904456482574 \tabularnewline
114 & 0.0194864688260535 & 0.0389729376521071 & 0.980513531173946 \tabularnewline
115 & 0.0167205137867927 & 0.0334410275735855 & 0.983279486213207 \tabularnewline
116 & 0.0158764652345523 & 0.0317529304691047 & 0.984123534765448 \tabularnewline
117 & 0.0190386649713257 & 0.0380773299426514 & 0.980961335028674 \tabularnewline
118 & 0.0225062337855732 & 0.0450124675711464 & 0.977493766214427 \tabularnewline
119 & 0.0203123951656872 & 0.0406247903313744 & 0.979687604834313 \tabularnewline
120 & 0.0172848831372967 & 0.0345697662745934 & 0.982715116862703 \tabularnewline
121 & 0.01545016703492 & 0.03090033406984 & 0.98454983296508 \tabularnewline
122 & 0.0157702713666751 & 0.0315405427333502 & 0.984229728633325 \tabularnewline
123 & 0.0182171124071051 & 0.0364342248142102 & 0.981782887592895 \tabularnewline
124 & 0.0205725006969574 & 0.0411450013939147 & 0.979427499303043 \tabularnewline
125 & 0.0185678428444629 & 0.0371356856889258 & 0.981432157155537 \tabularnewline
126 & 0.0165075672426146 & 0.0330151344852291 & 0.983492432757385 \tabularnewline
127 & 0.013155708395287 & 0.026311416790574 & 0.986844291604713 \tabularnewline
128 & 0.0104036670450059 & 0.0208073340900118 & 0.989596332954994 \tabularnewline
129 & 0.00840601377091857 & 0.0168120275418371 & 0.991593986229081 \tabularnewline
130 & 0.00888328015146153 & 0.0177665603029231 & 0.991116719848538 \tabularnewline
131 & 0.00980292259879723 & 0.0196058451975945 & 0.990197077401203 \tabularnewline
132 & 0.0107490377610788 & 0.0214980755221576 & 0.989250962238921 \tabularnewline
133 & 0.0110354987891474 & 0.0220709975782947 & 0.988964501210853 \tabularnewline
134 & 0.00909264500481455 & 0.0181852900096291 & 0.990907354995185 \tabularnewline
135 & 0.00722782968316258 & 0.0144556593663252 & 0.992772170316837 \tabularnewline
136 & 0.0103899253019732 & 0.0207798506039465 & 0.989610074698027 \tabularnewline
137 & 0.0133002648845775 & 0.026600529769155 & 0.986699735115423 \tabularnewline
138 & 0.0185107935803509 & 0.0370215871607019 & 0.981489206419649 \tabularnewline
139 & 0.0215185310413496 & 0.0430370620826992 & 0.97848146895865 \tabularnewline
140 & 0.0216570841725044 & 0.0433141683450088 & 0.978342915827496 \tabularnewline
141 & 0.0214294583815175 & 0.042858916763035 & 0.978570541618483 \tabularnewline
142 & 0.0314419329241415 & 0.0628838658482831 & 0.968558067075858 \tabularnewline
143 & 0.0380667185903442 & 0.0761334371806883 & 0.961933281409656 \tabularnewline
144 & 0.0358170842758963 & 0.0716341685517926 & 0.964182915724104 \tabularnewline
145 & 0.0347732409161457 & 0.0695464818322915 & 0.965226759083854 \tabularnewline
146 & 0.0366798964147861 & 0.0733597928295722 & 0.963320103585214 \tabularnewline
147 & 0.0518068495234324 & 0.103613699046865 & 0.948193150476568 \tabularnewline
148 & 0.0670938923779752 & 0.13418778475595 & 0.932906107622025 \tabularnewline
149 & 0.114789677946676 & 0.229579355893351 & 0.885210322053324 \tabularnewline
150 & 0.137359538272575 & 0.27471907654515 & 0.862640461727425 \tabularnewline
151 & 0.177650612140535 & 0.355301224281069 & 0.822349387859465 \tabularnewline
152 & 0.190380228697036 & 0.380760457394073 & 0.809619771302964 \tabularnewline
153 & 0.210322831926688 & 0.420645663853375 & 0.789677168073312 \tabularnewline
154 & 0.225647410483239 & 0.451294820966478 & 0.774352589516761 \tabularnewline
155 & 0.228817986601935 & 0.45763597320387 & 0.771182013398065 \tabularnewline
156 & 0.252139127993248 & 0.504278255986496 & 0.747860872006752 \tabularnewline
157 & 0.241764632199143 & 0.483529264398286 & 0.758235367800857 \tabularnewline
158 & 0.236937845572231 & 0.473875691144461 & 0.763062154427769 \tabularnewline
159 & 0.229376382239557 & 0.458752764479113 & 0.770623617760443 \tabularnewline
160 & 0.225896518327542 & 0.451793036655084 & 0.774103481672458 \tabularnewline
161 & 0.212461493712659 & 0.424922987425317 & 0.787538506287341 \tabularnewline
162 & 0.190218384827926 & 0.380436769655852 & 0.809781615172074 \tabularnewline
163 & 0.176106893042167 & 0.352213786084334 & 0.823893106957833 \tabularnewline
164 & 0.164060787212433 & 0.328121574424865 & 0.835939212787567 \tabularnewline
165 & 0.156047714146824 & 0.312095428293648 & 0.843952285853176 \tabularnewline
166 & 0.138679216095131 & 0.277358432190263 & 0.861320783904869 \tabularnewline
167 & 0.128869022558178 & 0.257738045116356 & 0.871130977441822 \tabularnewline
168 & 0.115449138093711 & 0.230898276187421 & 0.884550861906289 \tabularnewline
169 & 0.103422063280385 & 0.20684412656077 & 0.896577936719615 \tabularnewline
170 & 0.0958369158406339 & 0.191673831681268 & 0.904163084159366 \tabularnewline
171 & 0.0877800200058885 & 0.175560040011777 & 0.912219979994112 \tabularnewline
172 & 0.110369828898324 & 0.220739657796649 & 0.889630171101676 \tabularnewline
173 & 0.119944782952518 & 0.239889565905036 & 0.880055217047482 \tabularnewline
174 & 0.202650696004953 & 0.405301392009906 & 0.797349303995047 \tabularnewline
175 & 0.337015642313603 & 0.674031284627205 & 0.662984357686397 \tabularnewline
176 & 0.781163506816094 & 0.437672986367811 & 0.218836493183906 \tabularnewline
177 & 0.996630956482129 & 0.00673808703574151 & 0.00336904351787076 \tabularnewline
178 & 0.997472896464538 & 0.00505420707092458 & 0.00252710353546229 \tabularnewline
179 & 0.998461590957408 & 0.00307681808518453 & 0.00153840904259226 \tabularnewline
180 & 0.998909065179298 & 0.00218186964140386 & 0.00109093482070193 \tabularnewline
181 & 0.999079401254503 & 0.00184119749099353 & 0.000920598745496765 \tabularnewline
182 & 0.999219028293035 & 0.00156194341393002 & 0.000780971706965009 \tabularnewline
183 & 0.999188145223599 & 0.00162370955280191 & 0.000811854776400954 \tabularnewline
184 & 0.999216548681343 & 0.00156690263731404 & 0.00078345131865702 \tabularnewline
185 & 0.999327098117419 & 0.00134580376516129 & 0.000672901882580645 \tabularnewline
186 & 0.999183790881678 & 0.00163241823664416 & 0.000816209118322081 \tabularnewline
187 & 0.999036395117036 & 0.00192720976592718 & 0.000963604882963588 \tabularnewline
188 & 0.999055285628081 & 0.00188942874383843 & 0.000944714371919215 \tabularnewline
189 & 0.998989947959712 & 0.00202010408057648 & 0.00101005204028824 \tabularnewline
190 & 0.998931322191454 & 0.0021373556170923 & 0.00106867780854615 \tabularnewline
191 & 0.99905854206837 & 0.00188291586326028 & 0.000941457931630141 \tabularnewline
192 & 0.999600615281055 & 0.000798769437889479 & 0.00039938471894474 \tabularnewline
193 & 0.999528070372705 & 0.000943859254590298 & 0.000471929627295149 \tabularnewline
194 & 0.999377743452879 & 0.00124451309424226 & 0.000622256547121129 \tabularnewline
195 & 0.999237685002115 & 0.00152462999577045 & 0.000762314997885227 \tabularnewline
196 & 0.999062361346809 & 0.00187527730638209 & 0.000937638653191047 \tabularnewline
197 & 0.998742151674809 & 0.00251569665038295 & 0.00125784832519148 \tabularnewline
198 & 0.998515463993559 & 0.00296907201288132 & 0.00148453600644066 \tabularnewline
199 & 0.998319576077442 & 0.00336084784511514 & 0.00168042392255757 \tabularnewline
200 & 0.998159922446328 & 0.0036801551073444 & 0.0018400775536722 \tabularnewline
201 & 0.997717550590545 & 0.00456489881891087 & 0.00228244940945543 \tabularnewline
202 & 0.997019819666734 & 0.00596036066653222 & 0.00298018033326611 \tabularnewline
203 & 0.99661314750617 & 0.00677370498766063 & 0.00338685249383032 \tabularnewline
204 & 0.996444856348544 & 0.00711028730291232 & 0.00355514365145616 \tabularnewline
205 & 0.996235881768029 & 0.00752823646394201 & 0.003764118231971 \tabularnewline
206 & 0.995105551215169 & 0.0097888975696612 & 0.0048944487848306 \tabularnewline
207 & 0.995971079606905 & 0.00805784078619004 & 0.00402892039309502 \tabularnewline
208 & 0.994753998954194 & 0.0104920020916122 & 0.0052460010458061 \tabularnewline
209 & 0.992577430418997 & 0.0148451391620057 & 0.00742256958100283 \tabularnewline
210 & 0.98982098246352 & 0.0203580350729609 & 0.0101790175364804 \tabularnewline
211 & 0.98605284187091 & 0.0278943162581808 & 0.0139471581290904 \tabularnewline
212 & 0.981293489928659 & 0.0374130201426822 & 0.0187065100713411 \tabularnewline
213 & 0.974627065620128 & 0.050745868759744 & 0.025372934379872 \tabularnewline
214 & 0.969050206695386 & 0.0618995866092271 & 0.0309497933046135 \tabularnewline
215 & 0.958806599460714 & 0.082386801078572 & 0.041193400539286 \tabularnewline
216 & 0.948017377984656 & 0.103965244030688 & 0.0519826220153442 \tabularnewline
217 & 0.937833920040569 & 0.124332159918863 & 0.0621660799594313 \tabularnewline
218 & 0.925801124669033 & 0.148397750661934 & 0.0741988753309672 \tabularnewline
219 & 0.905712601500055 & 0.188574796999891 & 0.0942873984999454 \tabularnewline
220 & 0.88672284559289 & 0.226554308814221 & 0.11327715440711 \tabularnewline
221 & 0.862450142575013 & 0.275099714849974 & 0.137549857424987 \tabularnewline
222 & 0.835754239597294 & 0.328491520805412 & 0.164245760402706 \tabularnewline
223 & 0.870294649938842 & 0.259410700122315 & 0.129705350061158 \tabularnewline
224 & 0.918445092278146 & 0.163109815443709 & 0.0815549077218545 \tabularnewline
225 & 0.919197195352859 & 0.161605609294282 & 0.0808028046471408 \tabularnewline
226 & 0.907237369325659 & 0.185525261348681 & 0.0927626306743405 \tabularnewline
227 & 0.896634504875154 & 0.206730990249693 & 0.103365495124847 \tabularnewline
228 & 0.921777119971964 & 0.156445760056071 & 0.0782228800280356 \tabularnewline
229 & 0.967663569223029 & 0.0646728615539423 & 0.0323364307769712 \tabularnewline
230 & 0.996886755803629 & 0.00622648839274255 & 0.00311324419637127 \tabularnewline
231 & 0.998926690950686 & 0.00214661809862715 & 0.00107330904931357 \tabularnewline
232 & 0.998728887090019 & 0.00254222581996223 & 0.00127111290998112 \tabularnewline
233 & 0.998128404171538 & 0.00374319165692349 & 0.00187159582846175 \tabularnewline
234 & 0.997401527405506 & 0.00519694518898736 & 0.00259847259449368 \tabularnewline
235 & 0.996607188651996 & 0.00678562269600725 & 0.00339281134800363 \tabularnewline
236 & 0.994899182756202 & 0.0102016344875962 & 0.00510081724379809 \tabularnewline
237 & 0.991238074091904 & 0.0175238518161921 & 0.00876192590809606 \tabularnewline
238 & 0.985144510073014 & 0.0297109798539729 & 0.0148554899269865 \tabularnewline
239 & 0.976581150018234 & 0.0468376999635323 & 0.0234188499817662 \tabularnewline
240 & 0.964089501435694 & 0.0718209971286126 & 0.0359104985643063 \tabularnewline
241 & 0.963984270691833 & 0.0720314586163339 & 0.0360157293081669 \tabularnewline
242 & 0.996309506804399 & 0.00738098639120179 & 0.00369049319560089 \tabularnewline
243 & 0.99813038169168 & 0.00373923661663956 & 0.00186961830831978 \tabularnewline
244 & 0.998601540354327 & 0.00279691929134657 & 0.00139845964567329 \tabularnewline
245 & 0.996420883684776 & 0.00715823263044882 & 0.00357911631522441 \tabularnewline
246 & 0.991137814136195 & 0.0177243717276098 & 0.00886218586380491 \tabularnewline
247 & 0.999134654408967 & 0.00173069118206679 & 0.000865345591033395 \tabularnewline
248 & 0.99981981382741 & 0.000360372345179375 & 0.000180186172589688 \tabularnewline
249 & 0.999382454320431 & 0.001235091359137 & 0.0006175456795685 \tabularnewline
250 & 0.997101226035163 & 0.00579754792967294 & 0.00289877396483647 \tabularnewline
251 & 0.995795484922759 & 0.00840903015448203 & 0.00420451507724102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.00968496473431689[/C][C]0.0193699294686338[/C][C]0.990315035265683[/C][/ROW]
[ROW][C]9[/C][C]0.00437564624437096[/C][C]0.00875129248874191[/C][C]0.995624353755629[/C][/ROW]
[ROW][C]10[/C][C]0.000826683880822209[/C][C]0.00165336776164442[/C][C]0.999173316119178[/C][/ROW]
[ROW][C]11[/C][C]0.000171766538858718[/C][C]0.000343533077717436[/C][C]0.999828233461141[/C][/ROW]
[ROW][C]12[/C][C]0.00019671994664459[/C][C]0.000393439893289179[/C][C]0.999803280053355[/C][/ROW]
[ROW][C]13[/C][C]6.13833656487746e-05[/C][C]0.000122766731297549[/C][C]0.999938616634351[/C][/ROW]
[ROW][C]14[/C][C]1.39904755356717e-05[/C][C]2.79809510713435e-05[/C][C]0.999986009524464[/C][/ROW]
[ROW][C]15[/C][C]2.8310251682316e-06[/C][C]5.6620503364632e-06[/C][C]0.999997168974832[/C][/ROW]
[ROW][C]16[/C][C]5.67942284191735e-07[/C][C]1.13588456838347e-06[/C][C]0.999999432057716[/C][/ROW]
[ROW][C]17[/C][C]1.0651064453446e-07[/C][C]2.1302128906892e-07[/C][C]0.999999893489355[/C][/ROW]
[ROW][C]18[/C][C]2.53461703098142e-08[/C][C]5.06923406196283e-08[/C][C]0.99999997465383[/C][/ROW]
[ROW][C]19[/C][C]4.9489027405535e-09[/C][C]9.897805481107e-09[/C][C]0.999999995051097[/C][/ROW]
[ROW][C]20[/C][C]4.66418284070114e-09[/C][C]9.32836568140227e-09[/C][C]0.999999995335817[/C][/ROW]
[ROW][C]21[/C][C]9.12204117025081e-10[/C][C]1.82440823405016e-09[/C][C]0.999999999087796[/C][/ROW]
[ROW][C]22[/C][C]8.45627440261475e-10[/C][C]1.69125488052295e-09[/C][C]0.999999999154373[/C][/ROW]
[ROW][C]23[/C][C]1.64397482728504e-10[/C][C]3.28794965457008e-10[/C][C]0.999999999835603[/C][/ROW]
[ROW][C]24[/C][C]3.82309332112984e-11[/C][C]7.64618664225967e-11[/C][C]0.999999999961769[/C][/ROW]
[ROW][C]25[/C][C]1.10219876858871e-11[/C][C]2.20439753717742e-11[/C][C]0.999999999988978[/C][/ROW]
[ROW][C]26[/C][C]2.36749356569905e-12[/C][C]4.7349871313981e-12[/C][C]0.999999999997633[/C][/ROW]
[ROW][C]27[/C][C]4.78178498836949e-13[/C][C]9.56356997673897e-13[/C][C]0.999999999999522[/C][/ROW]
[ROW][C]28[/C][C]3.3006795113064e-13[/C][C]6.6013590226128e-13[/C][C]0.99999999999967[/C][/ROW]
[ROW][C]29[/C][C]1.86088414002388e-12[/C][C]3.72176828004776e-12[/C][C]0.999999999998139[/C][/ROW]
[ROW][C]30[/C][C]2.63636783467993e-11[/C][C]5.27273566935986e-11[/C][C]0.999999999973636[/C][/ROW]
[ROW][C]31[/C][C]6.75434933238049e-11[/C][C]1.3508698664761e-10[/C][C]0.999999999932456[/C][/ROW]
[ROW][C]32[/C][C]3.82971453059472e-11[/C][C]7.65942906118943e-11[/C][C]0.999999999961703[/C][/ROW]
[ROW][C]33[/C][C]2.92004503376198e-11[/C][C]5.84009006752396e-11[/C][C]0.9999999999708[/C][/ROW]
[ROW][C]34[/C][C]8.26741201321174e-12[/C][C]1.65348240264235e-11[/C][C]0.999999999991733[/C][/ROW]
[ROW][C]35[/C][C]4.52400485469285e-12[/C][C]9.04800970938571e-12[/C][C]0.999999999995476[/C][/ROW]
[ROW][C]36[/C][C]1.24711795023875e-11[/C][C]2.49423590047751e-11[/C][C]0.999999999987529[/C][/ROW]
[ROW][C]37[/C][C]5.84104941971563e-12[/C][C]1.16820988394313e-11[/C][C]0.999999999994159[/C][/ROW]
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[ROW][C]39[/C][C]9.93992712855076e-13[/C][C]1.98798542571015e-12[/C][C]0.999999999999006[/C][/ROW]
[ROW][C]40[/C][C]3.17738622694051e-13[/C][C]6.35477245388103e-13[/C][C]0.999999999999682[/C][/ROW]
[ROW][C]41[/C][C]2.71315313083135e-13[/C][C]5.42630626166269e-13[/C][C]0.999999999999729[/C][/ROW]
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[ROW][C]43[/C][C]1.10688853278645e-13[/C][C]2.21377706557289e-13[/C][C]0.999999999999889[/C][/ROW]
[ROW][C]44[/C][C]3.45083371196925e-14[/C][C]6.9016674239385e-14[/C][C]0.999999999999965[/C][/ROW]
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[ROW][C]47[/C][C]2.50761896438244e-15[/C][C]5.01523792876488e-15[/C][C]0.999999999999997[/C][/ROW]
[ROW][C]48[/C][C]4.17500695576183e-15[/C][C]8.35001391152365e-15[/C][C]0.999999999999996[/C][/ROW]
[ROW][C]49[/C][C]6.85102817111432e-15[/C][C]1.37020563422286e-14[/C][C]0.999999999999993[/C][/ROW]
[ROW][C]50[/C][C]1.66151249597993e-14[/C][C]3.32302499195986e-14[/C][C]0.999999999999983[/C][/ROW]
[ROW][C]51[/C][C]1.72008770346535e-14[/C][C]3.4401754069307e-14[/C][C]0.999999999999983[/C][/ROW]
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[ROW][C]53[/C][C]1.70161699170938e-14[/C][C]3.40323398341877e-14[/C][C]0.999999999999983[/C][/ROW]
[ROW][C]54[/C][C]1.1516827847658e-12[/C][C]2.3033655695316e-12[/C][C]0.999999999998848[/C][/ROW]
[ROW][C]55[/C][C]1.92313976482815e-12[/C][C]3.84627952965631e-12[/C][C]0.999999999998077[/C][/ROW]
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[ROW][C]57[/C][C]1.59799663408246e-12[/C][C]3.19599326816493e-12[/C][C]0.999999999998402[/C][/ROW]
[ROW][C]58[/C][C]1.35556255876958e-12[/C][C]2.71112511753915e-12[/C][C]0.999999999998644[/C][/ROW]
[ROW][C]59[/C][C]2.26192006423308e-12[/C][C]4.52384012846617e-12[/C][C]0.999999999997738[/C][/ROW]
[ROW][C]60[/C][C]2.26036148413248e-12[/C][C]4.52072296826495e-12[/C][C]0.99999999999774[/C][/ROW]
[ROW][C]61[/C][C]3.70640577571662e-12[/C][C]7.41281155143323e-12[/C][C]0.999999999996294[/C][/ROW]
[ROW][C]62[/C][C]6.52957379565497e-12[/C][C]1.30591475913099e-11[/C][C]0.99999999999347[/C][/ROW]
[ROW][C]63[/C][C]8.86721735679859e-12[/C][C]1.77344347135972e-11[/C][C]0.999999999991133[/C][/ROW]
[ROW][C]64[/C][C]1.28596806460455e-11[/C][C]2.57193612920911e-11[/C][C]0.99999999998714[/C][/ROW]
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[ROW][C]66[/C][C]4.64304740615254e-12[/C][C]9.28609481230508e-12[/C][C]0.999999999995357[/C][/ROW]
[ROW][C]67[/C][C]2.88143466772282e-12[/C][C]5.76286933544564e-12[/C][C]0.999999999997119[/C][/ROW]
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[ROW][C]90[/C][C]4.16996301062127e-05[/C][C]8.33992602124255e-05[/C][C]0.999958300369894[/C][/ROW]
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[ROW][C]161[/C][C]0.212461493712659[/C][C]0.424922987425317[/C][C]0.787538506287341[/C][/ROW]
[ROW][C]162[/C][C]0.190218384827926[/C][C]0.380436769655852[/C][C]0.809781615172074[/C][/ROW]
[ROW][C]163[/C][C]0.176106893042167[/C][C]0.352213786084334[/C][C]0.823893106957833[/C][/ROW]
[ROW][C]164[/C][C]0.164060787212433[/C][C]0.328121574424865[/C][C]0.835939212787567[/C][/ROW]
[ROW][C]165[/C][C]0.156047714146824[/C][C]0.312095428293648[/C][C]0.843952285853176[/C][/ROW]
[ROW][C]166[/C][C]0.138679216095131[/C][C]0.277358432190263[/C][C]0.861320783904869[/C][/ROW]
[ROW][C]167[/C][C]0.128869022558178[/C][C]0.257738045116356[/C][C]0.871130977441822[/C][/ROW]
[ROW][C]168[/C][C]0.115449138093711[/C][C]0.230898276187421[/C][C]0.884550861906289[/C][/ROW]
[ROW][C]169[/C][C]0.103422063280385[/C][C]0.20684412656077[/C][C]0.896577936719615[/C][/ROW]
[ROW][C]170[/C][C]0.0958369158406339[/C][C]0.191673831681268[/C][C]0.904163084159366[/C][/ROW]
[ROW][C]171[/C][C]0.0877800200058885[/C][C]0.175560040011777[/C][C]0.912219979994112[/C][/ROW]
[ROW][C]172[/C][C]0.110369828898324[/C][C]0.220739657796649[/C][C]0.889630171101676[/C][/ROW]
[ROW][C]173[/C][C]0.119944782952518[/C][C]0.239889565905036[/C][C]0.880055217047482[/C][/ROW]
[ROW][C]174[/C][C]0.202650696004953[/C][C]0.405301392009906[/C][C]0.797349303995047[/C][/ROW]
[ROW][C]175[/C][C]0.337015642313603[/C][C]0.674031284627205[/C][C]0.662984357686397[/C][/ROW]
[ROW][C]176[/C][C]0.781163506816094[/C][C]0.437672986367811[/C][C]0.218836493183906[/C][/ROW]
[ROW][C]177[/C][C]0.996630956482129[/C][C]0.00673808703574151[/C][C]0.00336904351787076[/C][/ROW]
[ROW][C]178[/C][C]0.997472896464538[/C][C]0.00505420707092458[/C][C]0.00252710353546229[/C][/ROW]
[ROW][C]179[/C][C]0.998461590957408[/C][C]0.00307681808518453[/C][C]0.00153840904259226[/C][/ROW]
[ROW][C]180[/C][C]0.998909065179298[/C][C]0.00218186964140386[/C][C]0.00109093482070193[/C][/ROW]
[ROW][C]181[/C][C]0.999079401254503[/C][C]0.00184119749099353[/C][C]0.000920598745496765[/C][/ROW]
[ROW][C]182[/C][C]0.999219028293035[/C][C]0.00156194341393002[/C][C]0.000780971706965009[/C][/ROW]
[ROW][C]183[/C][C]0.999188145223599[/C][C]0.00162370955280191[/C][C]0.000811854776400954[/C][/ROW]
[ROW][C]184[/C][C]0.999216548681343[/C][C]0.00156690263731404[/C][C]0.00078345131865702[/C][/ROW]
[ROW][C]185[/C][C]0.999327098117419[/C][C]0.00134580376516129[/C][C]0.000672901882580645[/C][/ROW]
[ROW][C]186[/C][C]0.999183790881678[/C][C]0.00163241823664416[/C][C]0.000816209118322081[/C][/ROW]
[ROW][C]187[/C][C]0.999036395117036[/C][C]0.00192720976592718[/C][C]0.000963604882963588[/C][/ROW]
[ROW][C]188[/C][C]0.999055285628081[/C][C]0.00188942874383843[/C][C]0.000944714371919215[/C][/ROW]
[ROW][C]189[/C][C]0.998989947959712[/C][C]0.00202010408057648[/C][C]0.00101005204028824[/C][/ROW]
[ROW][C]190[/C][C]0.998931322191454[/C][C]0.0021373556170923[/C][C]0.00106867780854615[/C][/ROW]
[ROW][C]191[/C][C]0.99905854206837[/C][C]0.00188291586326028[/C][C]0.000941457931630141[/C][/ROW]
[ROW][C]192[/C][C]0.999600615281055[/C][C]0.000798769437889479[/C][C]0.00039938471894474[/C][/ROW]
[ROW][C]193[/C][C]0.999528070372705[/C][C]0.000943859254590298[/C][C]0.000471929627295149[/C][/ROW]
[ROW][C]194[/C][C]0.999377743452879[/C][C]0.00124451309424226[/C][C]0.000622256547121129[/C][/ROW]
[ROW][C]195[/C][C]0.999237685002115[/C][C]0.00152462999577045[/C][C]0.000762314997885227[/C][/ROW]
[ROW][C]196[/C][C]0.999062361346809[/C][C]0.00187527730638209[/C][C]0.000937638653191047[/C][/ROW]
[ROW][C]197[/C][C]0.998742151674809[/C][C]0.00251569665038295[/C][C]0.00125784832519148[/C][/ROW]
[ROW][C]198[/C][C]0.998515463993559[/C][C]0.00296907201288132[/C][C]0.00148453600644066[/C][/ROW]
[ROW][C]199[/C][C]0.998319576077442[/C][C]0.00336084784511514[/C][C]0.00168042392255757[/C][/ROW]
[ROW][C]200[/C][C]0.998159922446328[/C][C]0.0036801551073444[/C][C]0.0018400775536722[/C][/ROW]
[ROW][C]201[/C][C]0.997717550590545[/C][C]0.00456489881891087[/C][C]0.00228244940945543[/C][/ROW]
[ROW][C]202[/C][C]0.997019819666734[/C][C]0.00596036066653222[/C][C]0.00298018033326611[/C][/ROW]
[ROW][C]203[/C][C]0.99661314750617[/C][C]0.00677370498766063[/C][C]0.00338685249383032[/C][/ROW]
[ROW][C]204[/C][C]0.996444856348544[/C][C]0.00711028730291232[/C][C]0.00355514365145616[/C][/ROW]
[ROW][C]205[/C][C]0.996235881768029[/C][C]0.00752823646394201[/C][C]0.003764118231971[/C][/ROW]
[ROW][C]206[/C][C]0.995105551215169[/C][C]0.0097888975696612[/C][C]0.0048944487848306[/C][/ROW]
[ROW][C]207[/C][C]0.995971079606905[/C][C]0.00805784078619004[/C][C]0.00402892039309502[/C][/ROW]
[ROW][C]208[/C][C]0.994753998954194[/C][C]0.0104920020916122[/C][C]0.0052460010458061[/C][/ROW]
[ROW][C]209[/C][C]0.992577430418997[/C][C]0.0148451391620057[/C][C]0.00742256958100283[/C][/ROW]
[ROW][C]210[/C][C]0.98982098246352[/C][C]0.0203580350729609[/C][C]0.0101790175364804[/C][/ROW]
[ROW][C]211[/C][C]0.98605284187091[/C][C]0.0278943162581808[/C][C]0.0139471581290904[/C][/ROW]
[ROW][C]212[/C][C]0.981293489928659[/C][C]0.0374130201426822[/C][C]0.0187065100713411[/C][/ROW]
[ROW][C]213[/C][C]0.974627065620128[/C][C]0.050745868759744[/C][C]0.025372934379872[/C][/ROW]
[ROW][C]214[/C][C]0.969050206695386[/C][C]0.0618995866092271[/C][C]0.0309497933046135[/C][/ROW]
[ROW][C]215[/C][C]0.958806599460714[/C][C]0.082386801078572[/C][C]0.041193400539286[/C][/ROW]
[ROW][C]216[/C][C]0.948017377984656[/C][C]0.103965244030688[/C][C]0.0519826220153442[/C][/ROW]
[ROW][C]217[/C][C]0.937833920040569[/C][C]0.124332159918863[/C][C]0.0621660799594313[/C][/ROW]
[ROW][C]218[/C][C]0.925801124669033[/C][C]0.148397750661934[/C][C]0.0741988753309672[/C][/ROW]
[ROW][C]219[/C][C]0.905712601500055[/C][C]0.188574796999891[/C][C]0.0942873984999454[/C][/ROW]
[ROW][C]220[/C][C]0.88672284559289[/C][C]0.226554308814221[/C][C]0.11327715440711[/C][/ROW]
[ROW][C]221[/C][C]0.862450142575013[/C][C]0.275099714849974[/C][C]0.137549857424987[/C][/ROW]
[ROW][C]222[/C][C]0.835754239597294[/C][C]0.328491520805412[/C][C]0.164245760402706[/C][/ROW]
[ROW][C]223[/C][C]0.870294649938842[/C][C]0.259410700122315[/C][C]0.129705350061158[/C][/ROW]
[ROW][C]224[/C][C]0.918445092278146[/C][C]0.163109815443709[/C][C]0.0815549077218545[/C][/ROW]
[ROW][C]225[/C][C]0.919197195352859[/C][C]0.161605609294282[/C][C]0.0808028046471408[/C][/ROW]
[ROW][C]226[/C][C]0.907237369325659[/C][C]0.185525261348681[/C][C]0.0927626306743405[/C][/ROW]
[ROW][C]227[/C][C]0.896634504875154[/C][C]0.206730990249693[/C][C]0.103365495124847[/C][/ROW]
[ROW][C]228[/C][C]0.921777119971964[/C][C]0.156445760056071[/C][C]0.0782228800280356[/C][/ROW]
[ROW][C]229[/C][C]0.967663569223029[/C][C]0.0646728615539423[/C][C]0.0323364307769712[/C][/ROW]
[ROW][C]230[/C][C]0.996886755803629[/C][C]0.00622648839274255[/C][C]0.00311324419637127[/C][/ROW]
[ROW][C]231[/C][C]0.998926690950686[/C][C]0.00214661809862715[/C][C]0.00107330904931357[/C][/ROW]
[ROW][C]232[/C][C]0.998728887090019[/C][C]0.00254222581996223[/C][C]0.00127111290998112[/C][/ROW]
[ROW][C]233[/C][C]0.998128404171538[/C][C]0.00374319165692349[/C][C]0.00187159582846175[/C][/ROW]
[ROW][C]234[/C][C]0.997401527405506[/C][C]0.00519694518898736[/C][C]0.00259847259449368[/C][/ROW]
[ROW][C]235[/C][C]0.996607188651996[/C][C]0.00678562269600725[/C][C]0.00339281134800363[/C][/ROW]
[ROW][C]236[/C][C]0.994899182756202[/C][C]0.0102016344875962[/C][C]0.00510081724379809[/C][/ROW]
[ROW][C]237[/C][C]0.991238074091904[/C][C]0.0175238518161921[/C][C]0.00876192590809606[/C][/ROW]
[ROW][C]238[/C][C]0.985144510073014[/C][C]0.0297109798539729[/C][C]0.0148554899269865[/C][/ROW]
[ROW][C]239[/C][C]0.976581150018234[/C][C]0.0468376999635323[/C][C]0.0234188499817662[/C][/ROW]
[ROW][C]240[/C][C]0.964089501435694[/C][C]0.0718209971286126[/C][C]0.0359104985643063[/C][/ROW]
[ROW][C]241[/C][C]0.963984270691833[/C][C]0.0720314586163339[/C][C]0.0360157293081669[/C][/ROW]
[ROW][C]242[/C][C]0.996309506804399[/C][C]0.00738098639120179[/C][C]0.00369049319560089[/C][/ROW]
[ROW][C]243[/C][C]0.99813038169168[/C][C]0.00373923661663956[/C][C]0.00186961830831978[/C][/ROW]
[ROW][C]244[/C][C]0.998601540354327[/C][C]0.00279691929134657[/C][C]0.00139845964567329[/C][/ROW]
[ROW][C]245[/C][C]0.996420883684776[/C][C]0.00715823263044882[/C][C]0.00357911631522441[/C][/ROW]
[ROW][C]246[/C][C]0.991137814136195[/C][C]0.0177243717276098[/C][C]0.00886218586380491[/C][/ROW]
[ROW][C]247[/C][C]0.999134654408967[/C][C]0.00173069118206679[/C][C]0.000865345591033395[/C][/ROW]
[ROW][C]248[/C][C]0.99981981382741[/C][C]0.000360372345179375[/C][C]0.000180186172589688[/C][/ROW]
[ROW][C]249[/C][C]0.999382454320431[/C][C]0.001235091359137[/C][C]0.0006175456795685[/C][/ROW]
[ROW][C]250[/C][C]0.997101226035163[/C][C]0.00579754792967294[/C][C]0.00289877396483647[/C][/ROW]
[ROW][C]251[/C][C]0.995795484922759[/C][C]0.00840903015448203[/C][C]0.00420451507724102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=5

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.009684964734316890.01936992946863380.990315035265683
90.004375646244370960.008751292488741910.995624353755629
100.0008266838808222090.001653367761644420.999173316119178
110.0001717665388587180.0003435330777174360.999828233461141
120.000196719946644590.0003934398932891790.999803280053355
136.13833656487746e-050.0001227667312975490.999938616634351
141.39904755356717e-052.79809510713435e-050.999986009524464
152.8310251682316e-065.6620503364632e-060.999997168974832
165.67942284191735e-071.13588456838347e-060.999999432057716
171.0651064453446e-072.1302128906892e-070.999999893489355
182.53461703098142e-085.06923406196283e-080.99999997465383
194.9489027405535e-099.897805481107e-090.999999995051097
204.66418284070114e-099.32836568140227e-090.999999995335817
219.12204117025081e-101.82440823405016e-090.999999999087796
228.45627440261475e-101.69125488052295e-090.999999999154373
231.64397482728504e-103.28794965457008e-100.999999999835603
243.82309332112984e-117.64618664225967e-110.999999999961769
251.10219876858871e-112.20439753717742e-110.999999999988978
262.36749356569905e-124.7349871313981e-120.999999999997633
274.78178498836949e-139.56356997673897e-130.999999999999522
283.3006795113064e-136.6013590226128e-130.99999999999967
291.86088414002388e-123.72176828004776e-120.999999999998139
302.63636783467993e-115.27273566935986e-110.999999999973636
316.75434933238049e-111.3508698664761e-100.999999999932456
323.82971453059472e-117.65942906118943e-110.999999999961703
332.92004503376198e-115.84009006752396e-110.9999999999708
348.26741201321174e-121.65348240264235e-110.999999999991733
354.52400485469285e-129.04800970938571e-120.999999999995476
361.24711795023875e-112.49423590047751e-110.999999999987529
375.84104941971563e-121.16820988394313e-110.999999999994159
383.22574136722902e-126.45148273445803e-120.999999999996774
399.93992712855076e-131.98798542571015e-120.999999999999006
403.17738622694051e-136.35477245388103e-130.999999999999682
412.71315313083135e-135.42630626166269e-130.999999999999729
422.04977373985681e-134.09954747971362e-130.999999999999795
431.10688853278645e-132.21377706557289e-130.999999999999889
443.45083371196925e-146.9016674239385e-140.999999999999965
451.67892552487513e-143.35785104975025e-140.999999999999983
467.14939088927257e-151.42987817785451e-140.999999999999993
472.50761896438244e-155.01523792876488e-150.999999999999997
484.17500695576183e-158.35001391152365e-150.999999999999996
496.85102817111432e-151.37020563422286e-140.999999999999993
501.66151249597993e-143.32302499195986e-140.999999999999983
511.72008770346535e-143.4401754069307e-140.999999999999983
521.49745628861167e-142.99491257722333e-140.999999999999985
531.70161699170938e-143.40323398341877e-140.999999999999983
541.1516827847658e-122.3033655695316e-120.999999999998848
551.92313976482815e-123.84627952965631e-120.999999999998077
561.55641139503275e-123.11282279006551e-120.999999999998444
571.59799663408246e-123.19599326816493e-120.999999999998402
581.35556255876958e-122.71112511753915e-120.999999999998644
592.26192006423308e-124.52384012846617e-120.999999999997738
602.26036148413248e-124.52072296826495e-120.99999999999774
613.70640577571662e-127.41281155143323e-120.999999999996294
626.52957379565497e-121.30591475913099e-110.99999999999347
638.86721735679859e-121.77344347135972e-110.999999999991133
641.28596806460455e-112.57193612920911e-110.99999999998714
658.69548501519817e-121.73909700303963e-110.999999999991305
664.64304740615254e-129.28609481230508e-120.999999999995357
672.88143466772282e-125.76286933544564e-120.999999999997119
681.26512485793485e-122.53024971586969e-120.999999999998735
696.95430587554209e-131.39086117510842e-120.999999999999305
703.04422116606028e-126.08844233212056e-120.999999999996956
712.71726804848503e-115.43453609697006e-110.999999999972827
726.47848463199081e-111.29569692639816e-100.999999999935215
732.24508492974733e-104.49016985949467e-100.999999999775491
744.42886551163408e-108.85773102326817e-100.999999999557113
759.12847896249464e-101.82569579249893e-090.999999999087152
761.06243893529058e-092.12487787058115e-090.999999998937561
771.5064368539811e-093.0128737079622e-090.999999998493563
783.85366466776972e-097.70732933553944e-090.999999996146335
794.36441414368529e-098.72882828737058e-090.999999995635586
806.55516201956571e-091.31103240391314e-080.999999993444838
819.11628180600799e-091.8232563612016e-080.999999990883718
822.2145406104161e-084.4290812208322e-080.999999977854594
836.58281492345454e-081.31656298469091e-070.999999934171851
848.26214264010691e-081.65242852802138e-070.999999917378574
853.34408593613617e-076.68817187227234e-070.999999665591406
862.16499908918572e-064.32999817837143e-060.999997835000911
874.5750877556312e-069.1501755112624e-060.999995424912244
887.10701371256759e-061.42140274251352e-050.999992892986287
891.75233422674932e-053.50466845349863e-050.999982476657733
904.16996301062127e-058.33992602124255e-050.999958300369894
910.0003993548052387390.0007987096104774780.999600645194761
920.0007053635397815080.001410727079563020.999294636460219
930.001507371349266010.003014742698532020.998492628650734
940.001403347520761240.002806695041522480.998596652479239
950.001194599996910210.002389199993820420.99880540000309
960.0009488593066994910.001897718613398980.9990511406933
970.001768773127453230.003537546254906460.998231226872547
980.005577305197248370.01115461039449670.994422694802752
990.008598002906695330.01719600581339070.991401997093305
1000.00905538774613960.01811077549227920.99094461225386
1010.008567729858447480.0171354597168950.991432270141553
1020.007954094890492320.01590818978098460.992045905109508
1030.006412404388531040.01282480877706210.993587595611469
1040.005291738153903440.01058347630780690.994708261846097
1050.005038048655157290.01007609731031460.994961951344843
1060.005207615860614640.01041523172122930.994792384139385
1070.004855014878261840.009710029756523680.995144985121738
1080.006290716535920860.01258143307184170.993709283464079
1090.008603249045710470.01720649809142090.99139675095429
1100.01010897958607330.02021795917214660.989891020413927
1110.02084103230440570.04168206460881130.979158967695594
1120.02744366980480330.05488733960960660.972556330195197
1130.0230955435174260.04619108703485190.976904456482574
1140.01948646882605350.03897293765210710.980513531173946
1150.01672051378679270.03344102757358550.983279486213207
1160.01587646523455230.03175293046910470.984123534765448
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1800.9989090651792980.002181869641403860.00109093482070193
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1880.9990552856280810.001889428743838430.000944714371919215
1890.9989899479597120.002020104080576480.00101005204028824
1900.9989313221914540.00213735561709230.00106867780854615
1910.999058542068370.001882915863260280.000941457931630141
1920.9996006152810550.0007987694378894790.00039938471894474
1930.9995280703727050.0009438592545902980.000471929627295149
1940.9993777434528790.001244513094242260.000622256547121129
1950.9992376850021150.001524629995770450.000762314997885227
1960.9990623613468090.001875277306382090.000937638653191047
1970.9987421516748090.002515696650382950.00125784832519148
1980.9985154639935590.002969072012881320.00148453600644066
1990.9983195760774420.003360847845115140.00168042392255757
2000.9981599224463280.00368015510734440.0018400775536722
2010.9977175505905450.004564898818910870.00228244940945543
2020.9970198196667340.005960360666532220.00298018033326611
2030.996613147506170.006773704987660630.00338685249383032
2040.9964448563485440.007110287302912320.00355514365145616
2050.9962358817680290.007528236463942010.003764118231971
2060.9951055512151690.00978889756966120.0048944487848306
2070.9959710796069050.008057840786190040.00402892039309502
2080.9947539989541940.01049200209161220.0052460010458061
2090.9925774304189970.01484513916200570.00742256958100283
2100.989820982463520.02035803507296090.0101790175364804
2110.986052841870910.02789431625818080.0139471581290904
2120.9812934899286590.03741302014268220.0187065100713411
2130.9746270656201280.0507458687597440.025372934379872
2140.9690502066953860.06189958660922710.0309497933046135
2150.9588065994607140.0823868010785720.041193400539286
2160.9480173779846560.1039652440306880.0519826220153442
2170.9378339200405690.1243321599188630.0621660799594313
2180.9258011246690330.1483977506619340.0741988753309672
2190.9057126015000550.1885747969998910.0942873984999454
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2230.8702946499388420.2594107001223150.129705350061158
2240.9184450922781460.1631098154437090.0815549077218545
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2500.9971012260351630.005797547929672940.00289877396483647
2510.9957954849227590.008409030154482030.00420451507724102






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1360.557377049180328NOK
5% type I error level1890.774590163934426NOK
10% type I error level2010.823770491803279NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 136 & 0.557377049180328 & NOK \tabularnewline
5% type I error level & 189 & 0.774590163934426 & NOK \tabularnewline
10% type I error level & 201 & 0.823770491803279 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201221&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]136[/C][C]0.557377049180328[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]189[/C][C]0.774590163934426[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]201[/C][C]0.823770491803279[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201221&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201221&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1360.557377049180328NOK
5% type I error level1890.774590163934426NOK
10% type I error level2010.823770491803279NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}