Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 26 Nov 2010 01:44:20 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/26/t1290735853tmp17uvn15vjmjz.htm/, Retrieved Mon, 29 Apr 2024 16:59:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101643, Retrieved Mon, 29 Apr 2024 16:59:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Aantal reizigers ...] [2010-11-26 01:03:33] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-    D        [Multiple Regression] [Aantal reizigers ...] [2010-11-26 01:44:20] [9ea95e194e0eb2a674315798620d5bc6] [Current]
-    D          [Multiple Regression] [Aantal reizigers ...] [2010-11-26 01:59:36] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-   PD            [Multiple Regression] [Regressiemodel] [2010-11-28 16:11:23] [39c51da0be01189e8a44eb69e891b7a1]
F   PD              [Multiple Regression] [autoregression wi...] [2010-11-30 16:17:19] [3df61981e9f4dafed65341be376c4457]
-   PD            [Multiple Regression] [model 2] [2010-11-28 16:10:50] [9f32078fdcdc094ca748857d5ebdb3de]
-   PD              [Multiple Regression] [] [2010-11-30 10:08:34] [ed939ef6f97e5f2afb6796311d9e7a5f]
-   PD            [Multiple Regression] [4 vertragingen - Ws8] [2010-11-30 21:32:25] [608064602fec1c42028cf50c6f981c88]
-   PD              [Multiple Regression] [4 vertragingen - ...] [2010-12-21 19:11:04] [608064602fec1c42028cf50c6f981c88]
- RMPD            [Exponential Smoothing] [] [2011-11-29 12:38:02] [06c08141d7d783218a8164fd2ea166f2]
- RMP             [Multiple Regression] [] [2011-11-29 15:39:13] [9401a40688cf36283be626153bc5a38b]
- RMP             [Multiple Regression] [incl. lags] [2011-11-29 21:05:16] [74be16979710d4c4e7c6647856088456]
- R P             [Multiple Regression] [HS8 Q6] [2012-11-27 11:20:27] [8eb8d17c2ec8c4c2abfbcde955accee7]
- RMPD            [Exponential Smoothing] [HS8 G7] [2012-11-27 11:34:33] [8eb8d17c2ec8c4c2abfbcde955accee7]
- R P           [Multiple Regression] [] [2011-11-29 15:33:31] [9401a40688cf36283be626153bc5a38b]
- RMP           [Multiple Regression] [incl. 9/11] [2011-11-29 21:02:24] [74be16979710d4c4e7c6647856088456]
- R P           [Multiple Regression] [HS8 G5] [2012-11-27 11:12:33] [8eb8d17c2ec8c4c2abfbcde955accee7]
Feedback Forum

Post a new message
Dataseries X:
0	1149822	1	0
0	1086979	2	0
0	1276674	3	0
0	1522522	4	0
0	1742117	5	0
0	1737275	6	0
0	1979900	7	0
0	2061036	8	0
0	1867943	9	0
0	1707752	10	0
0	1298756	11	0
0	1281814	12	0
0	1281151	13	0
0	1164976	14	0
0	1454329	15	0
0	1645288	16	0
0	1817743	17	0
0	1895785	18	0
0	2236311	19	0
0	2295951	20	0
0	2087315	21	0
0	1980891	22	0
0	1465446	23	0
0	1445026	24	0
0	1488120	25	0
0	1338333	26	0
0	1715789	27	0
0	1806090	28	0
0	2083316	29	0
0	2092278	30	0
0	2430800	31	0
0	2424894	32	0
0	2299016	33	0
0	2130688	34	0
0	1652221	35	0
0	1608162	36	0
0	1647074	37	0
0	1479691	38	0
0	1884978	39	0
0	2007898	40	0
0	2208954	41	0
0	2217164	42	0
0	2534291	43	0
0	2560312	44	0
0	2429069	45	0
0	2315077	46	0
0	1799608	47	0
0	1772590	48	0
0	1744799	49	0
0	1659093	50	0
0	2099821	51	0
0	2135736	52	0
0	2427894	53	0
0	2468882	54	0
0	2703217	55	0
0	2766841	56	0
0	2655236	57	0
0	2550373	58	0
0	2052097	59	0
0	1998055	60	0
0	1920748	61	0
0	1876694	62	0
0	2380930	63	0
0	2467402	64	0
0	2770771	65	0
0	2781340	66	0
0	3143926	67	0
0	3172235	68	0
0	2952540	69	0
0	2920877	70	0
0	2384552	71	0
0	2248987	72	0
0	2208616	73	0
0	2178756	74	0
0	2632870	75	0
0	2706905	76	0
0	3029745	77	0
0	3015402	78	0
0	3391414	79	0
0	3507805	80	0
0	3177852	81	0
0	3142961	82	0
0	2545815	83	0
0	2414007	84	0
0	2372578	85	0
0	2332664	86	0
0	2825328	87	0
0	2901478	88	0
0	3263955	89	0
0	3226738	90	0
0	3610786	91	0
0	3709274	92	0
0	3467185	93	0
0	3449646	94	0
0	2802951	95	0
0	2462530	96	0
0	2490645	97	0
0	2561520	98	0
0	3067554	99	0
0	3226951	100	0
0	3546493	101	0
0	3492787	102	0
0	3952263	103	0
0	3932072	104	0
0	3720284	105	0
0	3651555	106	0
0	2914972	107	0
0	2713514	108	0
0	2703997	109	0
0	2591373	110	0
0	3163748	111	0
0	3355137	112	0
0	3613702	113	0
0	3686773	114	0
0	4098716	115	0
0	4063517	116	0
1	3551489	117	117
1	3226663	118	118
1	2656842	119	119
1	2597484	120	120
1	2572399	121	121
1	2596631	122	122
1	3165225	123	123
1	3303145	124	124
1	3698247	125	125
1	3668631	126	126
1	4130433	127	127
1	4131400	128	128
1	3864358	129	129
1	3721110	130	130
1	2892532	131	131
1	2843451	132	132
1	2747502	133	133
1	2668775	134	134
1	3018602	135	135
1	3013392	136	136
1	3393657	137	137
1	3544233	138	138
1	4075832	139	139
1	4032923	140	140
1	3734509	141	141
1	3761285	142	142
1	2970090	143	143
1	2847849	144	144
1	2741680	145	145
1	2830639	146	146
1	3257673	147	147
1	3480085	148	148
1	3843271	149	149
1	3796961	150	150
1	4337767	151	151
1	4243630	152	152
1	3927202	153	153
1	3915296	154	154
1	3087396	155	155
1	2963792	156	156
1	2955792	157	157
1	2829925	158	158
1	3281195	159	159
1	3548011	160	160
1	4059648	161	161
1	3941175	162	162
1	4528594	163	163
1	4433151	164	164
1	4145737	165	165
1	4077132	166	166
1	3198519	167	167
1	3078660	168	168
1	3028202	169	169
1	2858642	170	170
1	3398954	171	171
1	3808883	172	172
1	4175961	173	173
1	4227542	174	174
1	4744616	175	175
1	4608012	176	176
1	4295049	177	177
1	4201144	178	178
1	3353276	179	179
1	3286851	180	180
1	3169889	181	181
1	3051720	182	182
1	3695426	183	183
1	3905501	184	184
1	4296458	185	185
1	4246247	186	186
1	4921849	187	187
1	4821446	188	188
1	4425064	189	189
1	4379099	190	190
1	3472889	191	191
1	3359160	192	192
1	3200944	193	193
1	3153170	194	194
1	3741498	195	195
1	3918719	196	196
1	4403449	197	197
1	4400407	198	198
1	4847473	199	199
1	4716136	200	200
1	4297440	201	201
1	4272253	202	202
1	3271834	203	203
1	3168388	204	204
1	2911748	205	205
1	2720999	206	206
1	3199918	207	207
1	3672623	208	208
1	3892013	209	209
1	3850845	210	210
1	4532467	211	211
1	4484739	212	212
1	4014972	213	213
1	3983758	214	214
1	3158459	215	215
1	3100569	216	216
1	2935404	217	217
1	2855719	218	218
1	3465611	219	219
1	3006985	220	220
1	4095110	221	221
1	4104793	222	222
1	4730788	223	223
1	4642726	224	224
1	4246919	225	225
1	4308117	226	226




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 14 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=0

As an alternative you can also use a 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 time14 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 851085.154504585 + 1269792.92126766`9/11`[t] + 17930.0832890866t -12135.7876863077`9/11_t`[t] -52753.3498852885M1[t] -140451.270586123M2[t] + 315252.650818305M3[t] + 445525.203801679M4[t] + 798067.493627159M5[t] + 787609.836084218M6[t] + 1224701.17854128M7[t] + 1195501.57362992M8[t] + 904434.402299098M9[t] + 815865.154634384M10[t] + 111160.300557044M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Yt[t] =  +  851085.154504585 +  1269792.92126766`9/11`[t] +  17930.0832890866t -12135.7876863077`9/11_t`[t] -52753.3498852885M1[t] -140451.270586123M2[t] +  315252.650818305M3[t] +  445525.203801679M4[t] +  798067.493627159M5[t] +  787609.836084218M6[t] +  1224701.17854128M7[t] +  1195501.57362992M8[t] +  904434.402299098M9[t] +  815865.154634384M10[t] +  111160.300557044M11[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Yt[t] =  +  851085.154504585 +  1269792.92126766`9/11`[t] +  17930.0832890866t -12135.7876863077`9/11_t`[t] -52753.3498852885M1[t] -140451.270586123M2[t] +  315252.650818305M3[t] +  445525.203801679M4[t] +  798067.493627159M5[t] +  787609.836084218M6[t] +  1224701.17854128M7[t] +  1195501.57362992M8[t] +  904434.402299098M9[t] +  815865.154634384M10[t] +  111160.300557044M11[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 851085.154504585 + 1269792.92126766`9/11`[t] + 17930.0832890866t -12135.7876863077`9/11_t`[t] -52753.3498852885M1[t] -140451.270586123M2[t] + 315252.650818305M3[t] + 445525.203801679M4[t] + 798067.493627159M5[t] + 787609.836084218M6[t] + 1224701.17854128M7[t] + 1195501.57362992M8[t] + 904434.402299098M9[t] + 815865.154634384M10[t] + 111160.300557044M11[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)851085.15450458553524.17742415.900900
`9/11`1269792.92126766101008.29210612.571200
t17930.0832890866503.47951435.612300
`9/11_t`-12135.7876863077741.901567-16.357700
M1-52753.349885288559686.709668-0.88380.377790.188895
M2-140451.27058612359683.39819-2.35330.0195290.009764
M3315252.65081830559682.3855215.282200
M4445525.20380167959683.6717787.464800
M5798067.49362715959687.25681213.370800
M6787609.83608421859693.14020813.194300
M71224701.1785412859701.32128720.513800
M81195501.5736299259711.79910520.021200
M9904434.40229909859681.67625915.154300
M10815865.15463438459683.80693313.669800
M11111160.30055704460470.3561661.83830.067430.033715

\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) & 851085.154504585 & 53524.177424 & 15.9009 & 0 & 0 \tabularnewline
`9/11` & 1269792.92126766 & 101008.292106 & 12.5712 & 0 & 0 \tabularnewline
t & 17930.0832890866 & 503.479514 & 35.6123 & 0 & 0 \tabularnewline
`9/11_t` & -12135.7876863077 & 741.901567 & -16.3577 & 0 & 0 \tabularnewline
M1 & -52753.3498852885 & 59686.709668 & -0.8838 & 0.37779 & 0.188895 \tabularnewline
M2 & -140451.270586123 & 59683.39819 & -2.3533 & 0.019529 & 0.009764 \tabularnewline
M3 & 315252.650818305 & 59682.385521 & 5.2822 & 0 & 0 \tabularnewline
M4 & 445525.203801679 & 59683.671778 & 7.4648 & 0 & 0 \tabularnewline
M5 & 798067.493627159 & 59687.256812 & 13.3708 & 0 & 0 \tabularnewline
M6 & 787609.836084218 & 59693.140208 & 13.1943 & 0 & 0 \tabularnewline
M7 & 1224701.17854128 & 59701.321287 & 20.5138 & 0 & 0 \tabularnewline
M8 & 1195501.57362992 & 59711.799105 & 20.0212 & 0 & 0 \tabularnewline
M9 & 904434.402299098 & 59681.676259 & 15.1543 & 0 & 0 \tabularnewline
M10 & 815865.154634384 & 59683.806933 & 13.6698 & 0 & 0 \tabularnewline
M11 & 111160.300557044 & 60470.356166 & 1.8383 & 0.06743 & 0.033715 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&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]851085.154504585[/C][C]53524.177424[/C][C]15.9009[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]`9/11`[/C][C]1269792.92126766[/C][C]101008.292106[/C][C]12.5712[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]t[/C][C]17930.0832890866[/C][C]503.479514[/C][C]35.6123[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]`9/11_t`[/C][C]-12135.7876863077[/C][C]741.901567[/C][C]-16.3577[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M1[/C][C]-52753.3498852885[/C][C]59686.709668[/C][C]-0.8838[/C][C]0.37779[/C][C]0.188895[/C][/ROW]
[ROW][C]M2[/C][C]-140451.270586123[/C][C]59683.39819[/C][C]-2.3533[/C][C]0.019529[/C][C]0.009764[/C][/ROW]
[ROW][C]M3[/C][C]315252.650818305[/C][C]59682.385521[/C][C]5.2822[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M4[/C][C]445525.203801679[/C][C]59683.671778[/C][C]7.4648[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M5[/C][C]798067.493627159[/C][C]59687.256812[/C][C]13.3708[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M6[/C][C]787609.836084218[/C][C]59693.140208[/C][C]13.1943[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M7[/C][C]1224701.17854128[/C][C]59701.321287[/C][C]20.5138[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M8[/C][C]1195501.57362992[/C][C]59711.799105[/C][C]20.0212[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M9[/C][C]904434.402299098[/C][C]59681.676259[/C][C]15.1543[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M10[/C][C]815865.154634384[/C][C]59683.806933[/C][C]13.6698[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M11[/C][C]111160.300557044[/C][C]60470.356166[/C][C]1.8383[/C][C]0.06743[/C][C]0.033715[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=2

As an alternative you can also use a 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)851085.15450458553524.17742415.900900
`9/11`1269792.92126766101008.29210612.571200
t17930.0832890866503.47951435.612300
`9/11_t`-12135.7876863077741.901567-16.357700
M1-52753.349885288559686.709668-0.88380.377790.188895
M2-140451.27058612359683.39819-2.35330.0195290.009764
M3315252.65081830559682.3855215.282200
M4445525.20380167959683.6717787.464800
M5798067.49362715959687.25681213.370800
M6787609.83608421859693.14020813.194300
M71224701.1785412859701.32128720.513800
M81195501.5736299259711.79910520.021200
M9904434.40229909859681.67625915.154300
M10815865.15463438459683.80693313.669800
M11111160.30055704460470.3561661.83830.067430.033715







Multiple Linear Regression - Regression Statistics
Multiple R0.981432822579366
R-squared0.963210385236102
Adjusted R-squared0.960769368142762
F-TEST (value)394.593871490865
F-TEST (DF numerator)14
F-TEST (DF denominator)211
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation181407.645579339
Sum Squared Residuals6943742847548.87

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.981432822579366 \tabularnewline
R-squared & 0.963210385236102 \tabularnewline
Adjusted R-squared & 0.960769368142762 \tabularnewline
F-TEST (value) & 394.593871490865 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 211 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 181407.645579339 \tabularnewline
Sum Squared Residuals & 6943742847548.87 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.981432822579366[/C][/ROW]
[ROW][C]R-squared[/C][C]0.963210385236102[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.960769368142762[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]394.593871490865[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]211[/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]181407.645579339[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]6943742847548.87[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.981432822579366
R-squared0.963210385236102
Adjusted R-squared0.960769368142762
F-TEST (value)394.593871490865
F-TEST (DF numerator)14
F-TEST (DF denominator)211
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation181407.645579339
Sum Squared Residuals6943742847548.87







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11149822816261.8879084333560.112091599
21086979746494.050496626340484.949503374
312766741220128.0551901556545.9448098508
415225221368330.69146261154191.308537389
517421171738803.064577183313.93542282109
617372751746275.49032332-9000.49032332417
719799002201296.91606947-221396.916069471
820610362190027.39444719-128991.394447193
918679431916890.30640546-48947.3064054626
1017077521846251.14202983-138499.142029834
1112987561159476.37124158139279.628758419
1212818141066246.15397362215567.846026375
1312811511031422.88737742249728.112622576
141164976961655.049965678203320.950034322
1514543291435289.0546591919039.9453408111
1616452881583491.6909316561796.3090683493
1718177431953964.06404622-136221.064046218
1818957851961436.48979236-65651.4897923634
1922363112416457.91553851-180146.915538509
2022959512405188.39391623-109237.393916234
2120873152132051.30587450-44736.3058745028
2219808912061412.14149888-80521.1414988753
2314654461374637.3707106290808.6292893783
2414450261281407.15344266163618.846557336
2514881201246583.88684646241536.113153537
2613383331176816.04943472161516.950565285
2717157891650450.0541282365338.9458717712
2818060901798652.690400697437.30959930965
2920833162169125.06351526-85809.063515257
3020922782176597.48926140-84319.4892614029
3124308002631618.91500755-200818.915007549
3224248942620349.39338527-195455.393385274
3322990162347212.30534354-48196.3053435425
3421306882276573.14096791-145885.140967915
3516522211589798.3701796662422.6298203386
3616081621496568.15291170111593.847088296
3716470741461744.88631550185329.113684498
3814796911391977.0489037587713.951096245
3918849781865611.0535972719366.9464027316
4020078982013813.68986973-5915.68986973007
4122089542384286.0629843-175332.062984297
4222171642391758.48873044-174594.488730443
4325342912846779.91447659-312488.914476588
4425603122835510.39285431-275198.392854313
4524290692562373.30481258-133304.304812582
4623150772491734.14043695-176657.140436955
4717996081804959.3696487-5351.3696487012
4817725901711729.1523807460860.8476192564
4917447991676905.8857845467893.1142154581
5016590931607138.0483727951954.9516272056
5120998212080772.0530663119048.9469336920
5221357362228974.68933877-93238.6893387697
5324278942599447.06245334-171553.062453337
5424688822606919.48819948-138037.488199482
5527032173061940.91394563-358723.913945628
5627668413050671.39232335-283830.392323352
5726552362777534.30428162-122298.304281622
5825503732706895.13990599-156522.139905994
5920520972020120.3691177431976.6308822592
6019980551926890.1518497871164.8481502167
6119207481892066.8852535828681.1147464185
6218766941822299.0478418354394.9521581658
6323809302295933.0525353584996.9474646523
6424674022444135.6888078123266.3111921906
6527707712814608.06192238-43837.061922376
6627813402822080.48766852-40740.4876685219
6731439263277101.91341467-133175.913414667
6831722353265832.39179239-93597.3917923924
6929525402992695.30375066-40155.3037506614
7029208772922056.13937503-1179.13937503405
7123845522235281.36858678149270.631413220
7222489872142051.15131882106935.848681177
7322086162107227.88472262101388.115277379
7421787562037460.04731087141295.952689126
7526328702511094.05200439121775.947995613
7627069052659296.6882768547608.311723151
7730297453029769.06139142-24.0613914158566
7830154023037241.48713756-21839.4871375617
7933914143492262.91288371-100848.912883707
8035078053480993.3912614326811.6087385679
8131778523207856.3032197-30004.3032197012
8231429613137217.138844075743.86115592631
8325458152450442.3680558295372.63194418
8424140072357212.1507878656794.8492121372
8523725782322388.8841916650189.1158083391
8623326642252621.0467799180042.9532200866
8728253282726255.0514734399072.948526573
8829014782874457.6877458927020.3122541113
8932639553244930.0608604619024.9391395444
9032267383252402.4866066-25664.4866066013
9136107863707423.91235275-96637.9123527469
9237092743696154.3907304713119.6092695282
9334671853423017.3026887444167.6973112593
9434496463352378.1383131197267.8616868867
9528029512665603.36752486137347.632475141
9624625302572373.1502569-109843.150256902
9724906452537549.8836607-46904.8836607006
9825615202467782.0462489593737.953751047
9930675542941416.05094247126137.949057533
10032269513089618.68721493137332.312785072
10135464933460091.0603294986401.939670505
10234927873467563.4860756425223.5139243592
10339522633922584.9118217929678.0881782135
10439320723911315.3901995120756.6098004885
10537202843638178.3021577882105.6978422197
10636515553567539.1377821584015.8622178469
10729149722880764.366993934207.6330061006
10827135142787534.14972594-74020.149725942
10927039972752710.88312974-48713.8831297401
11025913732682943.04571799-91570.0457179927
11131637483156577.050411517170.9495884936
11233551373304779.6866839750357.313316032
11336137023675252.05979853-61550.0597985347
11436867733682724.485544684048.51445531931
11540987164137745.91129083-39029.9112908264
11640635174126476.38966855-62959.3896685509
11735514893703245.06359648-151756.063596479
11832266633620470.11153454-393807.111534544
11926568422921559.55305998-264717.553059982
12025974842816193.54810572-218709.548105718
12125723992769234.49382321-196835.493823208
12225966312687330.86872515-90699.8687251525
12331652253148829.0857323616395.9142676415
12433031453284895.9343185118249.0656814877
12536982473643232.5197467755014.4802532287
12636686313638569.1578066130061.8421933905
12741304334081454.7958664548978.2041335522
12841314004058049.4865578673350.5134421357
12938643583772776.6108298391581.3891701742
13037211103690001.6587678931108.3412321093
13128925322991091.10029333-98559.1002933295
13228434512885725.09533906-42274.0953390645
13327475022838766.04105655-91264.0410565549
13426687752756862.4159585-88087.4159584995
13530186023218360.63296571-199758.632965706
13630133923354427.48155186-341035.481551859
13733936573712764.06698012-319107.066980118
13835442333708100.70503996-163867.705039957
13940758324150986.34309979-75154.3430997945
14040329234127581.03379121-94658.0337912118
14137345093842308.15806317-107799.158063173
14237612853759533.206001241751.79399876225
14329700903060622.64752668-90532.6475266765
14428478492955256.64257241-107407.642572411
14527416802908297.5882899-166617.588289902
14628306392826393.963191854245.03680815336
14732576733287892.18019905-30219.1801990526
14834800853423959.0287852156125.9712147934
14938432713782295.6142134760975.3857865343
15037969613777632.252273319328.7477266964
15143377674220517.89033314117249.109666859
15242436304197112.5810245646517.4189754411
15339272023911839.7052965215362.2947034800
15439152963829064.7532345886231.2467654155
15530873963130154.19476002-42758.1947600235
15629637923024788.18980576-60996.1898057584
15729557922977829.13552325-22037.1355232488
15828299252895925.51042519-66000.5104251937
15932811953357423.7274324-76228.7274323997
16035480113493490.5760185554520.4239814465
16140596483851827.16144681207820.838553187
16239411753847163.7995066594011.2004933491
16345285944290049.43756649238544.562433511
16444331514266644.12825791166506.871742094
16541457373981371.25252987164365.747470133
16640771323898596.30046793178535.699532068
16731985193199685.74199337-1166.74199337055
16830786603094319.73703911-15659.7370391055
16930282023047360.68275660-19158.6827565959
17028586422965457.05765854-106815.057658541
17133989543426955.27466575-28001.2746657467
17238088833563022.1232519245860.876748099
17341759613921358.70868016254602.291319841
17442275423916695.34674310846.653260002
17547446164359580.98479984385035.015200164
17646080124336175.67549125271836.324508747
17742950494050902.79976321244146.200236786
17842011443968127.84770128233016.152298721
17933532763269217.2892267284058.7107732822
18032868513163851.28427245122999.715727548
18131698893116892.2299899452996.770010057
18230517203034988.6048918916731.3951081122
18336954263496486.82189909198939.178100906
18439055013632553.67048525272947.329514752
18542964583990890.25591351305567.744086493
18642462473986226.89397334260020.106026655
18749218494429112.53203318492736.467966817
18848214464405707.2227246415738.7772754
18944250644120434.34699656304629.653003439
19043790994037659.39493463341439.605065374
19134728893338748.83646006134140.163539935
19233591603233382.8315058125777.168494201
19332009443186423.7772232914520.2227767100
19431531703104520.1521252348649.8478747652
19537414983566018.36913244175479.630867559
19639187193702085.21771859216633.782281405
19744034494060421.80314685343027.196853146
19844004074055758.44120669344648.558793308
19948474734498644.07926653348828.92073347
20047161364475238.76995795240897.230042053
20142974404189965.89422991107474.105770092
20242722534107190.94216797165062.057832027
20332718343408280.38369341-136446.383693411
20431683883302914.37873915-134526.378739147
20529117483255955.32445664-344207.324456637
20627209993174051.69935858-453052.699358582
20731999183635549.91636579-435631.916365788
20836726233771616.76495194-98993.7649519414
20938920134129953.3503802-237940.350380200
21038508454125289.98844004-274444.988440038
21145324674568175.62649988-35708.6264998764
21244847394544770.31719129-60031.3171912936
21340149724259497.44146325-244525.441463255
21439837584176722.48940132-192964.489401320
21531584593477811.93092676-319352.930926759
21631005693372445.92597249-271876.925972493
21729354043325486.87168998-390082.871689984
21828557193243583.24659193-387864.246591928
21934656113705081.46359913-239470.463599135
22030069853841148.31218529-834163.312185289
22140951104199484.89761355-104374.897613548
22241047934194821.53567339-90028.5356733855
22347307884637707.1737332293080.8262667766
22446427264614301.8644246428424.1355753594
22542469194329028.9886966-82109.9886966021
22643081174246254.0366346761862.9633653331

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1149822 & 816261.8879084 & 333560.112091599 \tabularnewline
2 & 1086979 & 746494.050496626 & 340484.949503374 \tabularnewline
3 & 1276674 & 1220128.05519015 & 56545.9448098508 \tabularnewline
4 & 1522522 & 1368330.69146261 & 154191.308537389 \tabularnewline
5 & 1742117 & 1738803.06457718 & 3313.93542282109 \tabularnewline
6 & 1737275 & 1746275.49032332 & -9000.49032332417 \tabularnewline
7 & 1979900 & 2201296.91606947 & -221396.916069471 \tabularnewline
8 & 2061036 & 2190027.39444719 & -128991.394447193 \tabularnewline
9 & 1867943 & 1916890.30640546 & -48947.3064054626 \tabularnewline
10 & 1707752 & 1846251.14202983 & -138499.142029834 \tabularnewline
11 & 1298756 & 1159476.37124158 & 139279.628758419 \tabularnewline
12 & 1281814 & 1066246.15397362 & 215567.846026375 \tabularnewline
13 & 1281151 & 1031422.88737742 & 249728.112622576 \tabularnewline
14 & 1164976 & 961655.049965678 & 203320.950034322 \tabularnewline
15 & 1454329 & 1435289.05465919 & 19039.9453408111 \tabularnewline
16 & 1645288 & 1583491.69093165 & 61796.3090683493 \tabularnewline
17 & 1817743 & 1953964.06404622 & -136221.064046218 \tabularnewline
18 & 1895785 & 1961436.48979236 & -65651.4897923634 \tabularnewline
19 & 2236311 & 2416457.91553851 & -180146.915538509 \tabularnewline
20 & 2295951 & 2405188.39391623 & -109237.393916234 \tabularnewline
21 & 2087315 & 2132051.30587450 & -44736.3058745028 \tabularnewline
22 & 1980891 & 2061412.14149888 & -80521.1414988753 \tabularnewline
23 & 1465446 & 1374637.37071062 & 90808.6292893783 \tabularnewline
24 & 1445026 & 1281407.15344266 & 163618.846557336 \tabularnewline
25 & 1488120 & 1246583.88684646 & 241536.113153537 \tabularnewline
26 & 1338333 & 1176816.04943472 & 161516.950565285 \tabularnewline
27 & 1715789 & 1650450.05412823 & 65338.9458717712 \tabularnewline
28 & 1806090 & 1798652.69040069 & 7437.30959930965 \tabularnewline
29 & 2083316 & 2169125.06351526 & -85809.063515257 \tabularnewline
30 & 2092278 & 2176597.48926140 & -84319.4892614029 \tabularnewline
31 & 2430800 & 2631618.91500755 & -200818.915007549 \tabularnewline
32 & 2424894 & 2620349.39338527 & -195455.393385274 \tabularnewline
33 & 2299016 & 2347212.30534354 & -48196.3053435425 \tabularnewline
34 & 2130688 & 2276573.14096791 & -145885.140967915 \tabularnewline
35 & 1652221 & 1589798.37017966 & 62422.6298203386 \tabularnewline
36 & 1608162 & 1496568.15291170 & 111593.847088296 \tabularnewline
37 & 1647074 & 1461744.88631550 & 185329.113684498 \tabularnewline
38 & 1479691 & 1391977.04890375 & 87713.951096245 \tabularnewline
39 & 1884978 & 1865611.05359727 & 19366.9464027316 \tabularnewline
40 & 2007898 & 2013813.68986973 & -5915.68986973007 \tabularnewline
41 & 2208954 & 2384286.0629843 & -175332.062984297 \tabularnewline
42 & 2217164 & 2391758.48873044 & -174594.488730443 \tabularnewline
43 & 2534291 & 2846779.91447659 & -312488.914476588 \tabularnewline
44 & 2560312 & 2835510.39285431 & -275198.392854313 \tabularnewline
45 & 2429069 & 2562373.30481258 & -133304.304812582 \tabularnewline
46 & 2315077 & 2491734.14043695 & -176657.140436955 \tabularnewline
47 & 1799608 & 1804959.3696487 & -5351.3696487012 \tabularnewline
48 & 1772590 & 1711729.15238074 & 60860.8476192564 \tabularnewline
49 & 1744799 & 1676905.88578454 & 67893.1142154581 \tabularnewline
50 & 1659093 & 1607138.04837279 & 51954.9516272056 \tabularnewline
51 & 2099821 & 2080772.05306631 & 19048.9469336920 \tabularnewline
52 & 2135736 & 2228974.68933877 & -93238.6893387697 \tabularnewline
53 & 2427894 & 2599447.06245334 & -171553.062453337 \tabularnewline
54 & 2468882 & 2606919.48819948 & -138037.488199482 \tabularnewline
55 & 2703217 & 3061940.91394563 & -358723.913945628 \tabularnewline
56 & 2766841 & 3050671.39232335 & -283830.392323352 \tabularnewline
57 & 2655236 & 2777534.30428162 & -122298.304281622 \tabularnewline
58 & 2550373 & 2706895.13990599 & -156522.139905994 \tabularnewline
59 & 2052097 & 2020120.36911774 & 31976.6308822592 \tabularnewline
60 & 1998055 & 1926890.15184978 & 71164.8481502167 \tabularnewline
61 & 1920748 & 1892066.88525358 & 28681.1147464185 \tabularnewline
62 & 1876694 & 1822299.04784183 & 54394.9521581658 \tabularnewline
63 & 2380930 & 2295933.05253535 & 84996.9474646523 \tabularnewline
64 & 2467402 & 2444135.68880781 & 23266.3111921906 \tabularnewline
65 & 2770771 & 2814608.06192238 & -43837.061922376 \tabularnewline
66 & 2781340 & 2822080.48766852 & -40740.4876685219 \tabularnewline
67 & 3143926 & 3277101.91341467 & -133175.913414667 \tabularnewline
68 & 3172235 & 3265832.39179239 & -93597.3917923924 \tabularnewline
69 & 2952540 & 2992695.30375066 & -40155.3037506614 \tabularnewline
70 & 2920877 & 2922056.13937503 & -1179.13937503405 \tabularnewline
71 & 2384552 & 2235281.36858678 & 149270.631413220 \tabularnewline
72 & 2248987 & 2142051.15131882 & 106935.848681177 \tabularnewline
73 & 2208616 & 2107227.88472262 & 101388.115277379 \tabularnewline
74 & 2178756 & 2037460.04731087 & 141295.952689126 \tabularnewline
75 & 2632870 & 2511094.05200439 & 121775.947995613 \tabularnewline
76 & 2706905 & 2659296.68827685 & 47608.311723151 \tabularnewline
77 & 3029745 & 3029769.06139142 & -24.0613914158566 \tabularnewline
78 & 3015402 & 3037241.48713756 & -21839.4871375617 \tabularnewline
79 & 3391414 & 3492262.91288371 & -100848.912883707 \tabularnewline
80 & 3507805 & 3480993.39126143 & 26811.6087385679 \tabularnewline
81 & 3177852 & 3207856.3032197 & -30004.3032197012 \tabularnewline
82 & 3142961 & 3137217.13884407 & 5743.86115592631 \tabularnewline
83 & 2545815 & 2450442.36805582 & 95372.63194418 \tabularnewline
84 & 2414007 & 2357212.15078786 & 56794.8492121372 \tabularnewline
85 & 2372578 & 2322388.88419166 & 50189.1158083391 \tabularnewline
86 & 2332664 & 2252621.04677991 & 80042.9532200866 \tabularnewline
87 & 2825328 & 2726255.05147343 & 99072.948526573 \tabularnewline
88 & 2901478 & 2874457.68774589 & 27020.3122541113 \tabularnewline
89 & 3263955 & 3244930.06086046 & 19024.9391395444 \tabularnewline
90 & 3226738 & 3252402.4866066 & -25664.4866066013 \tabularnewline
91 & 3610786 & 3707423.91235275 & -96637.9123527469 \tabularnewline
92 & 3709274 & 3696154.39073047 & 13119.6092695282 \tabularnewline
93 & 3467185 & 3423017.30268874 & 44167.6973112593 \tabularnewline
94 & 3449646 & 3352378.13831311 & 97267.8616868867 \tabularnewline
95 & 2802951 & 2665603.36752486 & 137347.632475141 \tabularnewline
96 & 2462530 & 2572373.1502569 & -109843.150256902 \tabularnewline
97 & 2490645 & 2537549.8836607 & -46904.8836607006 \tabularnewline
98 & 2561520 & 2467782.04624895 & 93737.953751047 \tabularnewline
99 & 3067554 & 2941416.05094247 & 126137.949057533 \tabularnewline
100 & 3226951 & 3089618.68721493 & 137332.312785072 \tabularnewline
101 & 3546493 & 3460091.06032949 & 86401.939670505 \tabularnewline
102 & 3492787 & 3467563.48607564 & 25223.5139243592 \tabularnewline
103 & 3952263 & 3922584.91182179 & 29678.0881782135 \tabularnewline
104 & 3932072 & 3911315.39019951 & 20756.6098004885 \tabularnewline
105 & 3720284 & 3638178.30215778 & 82105.6978422197 \tabularnewline
106 & 3651555 & 3567539.13778215 & 84015.8622178469 \tabularnewline
107 & 2914972 & 2880764.3669939 & 34207.6330061006 \tabularnewline
108 & 2713514 & 2787534.14972594 & -74020.149725942 \tabularnewline
109 & 2703997 & 2752710.88312974 & -48713.8831297401 \tabularnewline
110 & 2591373 & 2682943.04571799 & -91570.0457179927 \tabularnewline
111 & 3163748 & 3156577.05041151 & 7170.9495884936 \tabularnewline
112 & 3355137 & 3304779.68668397 & 50357.313316032 \tabularnewline
113 & 3613702 & 3675252.05979853 & -61550.0597985347 \tabularnewline
114 & 3686773 & 3682724.48554468 & 4048.51445531931 \tabularnewline
115 & 4098716 & 4137745.91129083 & -39029.9112908264 \tabularnewline
116 & 4063517 & 4126476.38966855 & -62959.3896685509 \tabularnewline
117 & 3551489 & 3703245.06359648 & -151756.063596479 \tabularnewline
118 & 3226663 & 3620470.11153454 & -393807.111534544 \tabularnewline
119 & 2656842 & 2921559.55305998 & -264717.553059982 \tabularnewline
120 & 2597484 & 2816193.54810572 & -218709.548105718 \tabularnewline
121 & 2572399 & 2769234.49382321 & -196835.493823208 \tabularnewline
122 & 2596631 & 2687330.86872515 & -90699.8687251525 \tabularnewline
123 & 3165225 & 3148829.08573236 & 16395.9142676415 \tabularnewline
124 & 3303145 & 3284895.93431851 & 18249.0656814877 \tabularnewline
125 & 3698247 & 3643232.51974677 & 55014.4802532287 \tabularnewline
126 & 3668631 & 3638569.15780661 & 30061.8421933905 \tabularnewline
127 & 4130433 & 4081454.79586645 & 48978.2041335522 \tabularnewline
128 & 4131400 & 4058049.48655786 & 73350.5134421357 \tabularnewline
129 & 3864358 & 3772776.61082983 & 91581.3891701742 \tabularnewline
130 & 3721110 & 3690001.65876789 & 31108.3412321093 \tabularnewline
131 & 2892532 & 2991091.10029333 & -98559.1002933295 \tabularnewline
132 & 2843451 & 2885725.09533906 & -42274.0953390645 \tabularnewline
133 & 2747502 & 2838766.04105655 & -91264.0410565549 \tabularnewline
134 & 2668775 & 2756862.4159585 & -88087.4159584995 \tabularnewline
135 & 3018602 & 3218360.63296571 & -199758.632965706 \tabularnewline
136 & 3013392 & 3354427.48155186 & -341035.481551859 \tabularnewline
137 & 3393657 & 3712764.06698012 & -319107.066980118 \tabularnewline
138 & 3544233 & 3708100.70503996 & -163867.705039957 \tabularnewline
139 & 4075832 & 4150986.34309979 & -75154.3430997945 \tabularnewline
140 & 4032923 & 4127581.03379121 & -94658.0337912118 \tabularnewline
141 & 3734509 & 3842308.15806317 & -107799.158063173 \tabularnewline
142 & 3761285 & 3759533.20600124 & 1751.79399876225 \tabularnewline
143 & 2970090 & 3060622.64752668 & -90532.6475266765 \tabularnewline
144 & 2847849 & 2955256.64257241 & -107407.642572411 \tabularnewline
145 & 2741680 & 2908297.5882899 & -166617.588289902 \tabularnewline
146 & 2830639 & 2826393.96319185 & 4245.03680815336 \tabularnewline
147 & 3257673 & 3287892.18019905 & -30219.1801990526 \tabularnewline
148 & 3480085 & 3423959.02878521 & 56125.9712147934 \tabularnewline
149 & 3843271 & 3782295.61421347 & 60975.3857865343 \tabularnewline
150 & 3796961 & 3777632.2522733 & 19328.7477266964 \tabularnewline
151 & 4337767 & 4220517.89033314 & 117249.109666859 \tabularnewline
152 & 4243630 & 4197112.58102456 & 46517.4189754411 \tabularnewline
153 & 3927202 & 3911839.70529652 & 15362.2947034800 \tabularnewline
154 & 3915296 & 3829064.75323458 & 86231.2467654155 \tabularnewline
155 & 3087396 & 3130154.19476002 & -42758.1947600235 \tabularnewline
156 & 2963792 & 3024788.18980576 & -60996.1898057584 \tabularnewline
157 & 2955792 & 2977829.13552325 & -22037.1355232488 \tabularnewline
158 & 2829925 & 2895925.51042519 & -66000.5104251937 \tabularnewline
159 & 3281195 & 3357423.7274324 & -76228.7274323997 \tabularnewline
160 & 3548011 & 3493490.57601855 & 54520.4239814465 \tabularnewline
161 & 4059648 & 3851827.16144681 & 207820.838553187 \tabularnewline
162 & 3941175 & 3847163.79950665 & 94011.2004933491 \tabularnewline
163 & 4528594 & 4290049.43756649 & 238544.562433511 \tabularnewline
164 & 4433151 & 4266644.12825791 & 166506.871742094 \tabularnewline
165 & 4145737 & 3981371.25252987 & 164365.747470133 \tabularnewline
166 & 4077132 & 3898596.30046793 & 178535.699532068 \tabularnewline
167 & 3198519 & 3199685.74199337 & -1166.74199337055 \tabularnewline
168 & 3078660 & 3094319.73703911 & -15659.7370391055 \tabularnewline
169 & 3028202 & 3047360.68275660 & -19158.6827565959 \tabularnewline
170 & 2858642 & 2965457.05765854 & -106815.057658541 \tabularnewline
171 & 3398954 & 3426955.27466575 & -28001.2746657467 \tabularnewline
172 & 3808883 & 3563022.1232519 & 245860.876748099 \tabularnewline
173 & 4175961 & 3921358.70868016 & 254602.291319841 \tabularnewline
174 & 4227542 & 3916695.34674 & 310846.653260002 \tabularnewline
175 & 4744616 & 4359580.98479984 & 385035.015200164 \tabularnewline
176 & 4608012 & 4336175.67549125 & 271836.324508747 \tabularnewline
177 & 4295049 & 4050902.79976321 & 244146.200236786 \tabularnewline
178 & 4201144 & 3968127.84770128 & 233016.152298721 \tabularnewline
179 & 3353276 & 3269217.28922672 & 84058.7107732822 \tabularnewline
180 & 3286851 & 3163851.28427245 & 122999.715727548 \tabularnewline
181 & 3169889 & 3116892.22998994 & 52996.770010057 \tabularnewline
182 & 3051720 & 3034988.60489189 & 16731.3951081122 \tabularnewline
183 & 3695426 & 3496486.82189909 & 198939.178100906 \tabularnewline
184 & 3905501 & 3632553.67048525 & 272947.329514752 \tabularnewline
185 & 4296458 & 3990890.25591351 & 305567.744086493 \tabularnewline
186 & 4246247 & 3986226.89397334 & 260020.106026655 \tabularnewline
187 & 4921849 & 4429112.53203318 & 492736.467966817 \tabularnewline
188 & 4821446 & 4405707.2227246 & 415738.7772754 \tabularnewline
189 & 4425064 & 4120434.34699656 & 304629.653003439 \tabularnewline
190 & 4379099 & 4037659.39493463 & 341439.605065374 \tabularnewline
191 & 3472889 & 3338748.83646006 & 134140.163539935 \tabularnewline
192 & 3359160 & 3233382.8315058 & 125777.168494201 \tabularnewline
193 & 3200944 & 3186423.77722329 & 14520.2227767100 \tabularnewline
194 & 3153170 & 3104520.15212523 & 48649.8478747652 \tabularnewline
195 & 3741498 & 3566018.36913244 & 175479.630867559 \tabularnewline
196 & 3918719 & 3702085.21771859 & 216633.782281405 \tabularnewline
197 & 4403449 & 4060421.80314685 & 343027.196853146 \tabularnewline
198 & 4400407 & 4055758.44120669 & 344648.558793308 \tabularnewline
199 & 4847473 & 4498644.07926653 & 348828.92073347 \tabularnewline
200 & 4716136 & 4475238.76995795 & 240897.230042053 \tabularnewline
201 & 4297440 & 4189965.89422991 & 107474.105770092 \tabularnewline
202 & 4272253 & 4107190.94216797 & 165062.057832027 \tabularnewline
203 & 3271834 & 3408280.38369341 & -136446.383693411 \tabularnewline
204 & 3168388 & 3302914.37873915 & -134526.378739147 \tabularnewline
205 & 2911748 & 3255955.32445664 & -344207.324456637 \tabularnewline
206 & 2720999 & 3174051.69935858 & -453052.699358582 \tabularnewline
207 & 3199918 & 3635549.91636579 & -435631.916365788 \tabularnewline
208 & 3672623 & 3771616.76495194 & -98993.7649519414 \tabularnewline
209 & 3892013 & 4129953.3503802 & -237940.350380200 \tabularnewline
210 & 3850845 & 4125289.98844004 & -274444.988440038 \tabularnewline
211 & 4532467 & 4568175.62649988 & -35708.6264998764 \tabularnewline
212 & 4484739 & 4544770.31719129 & -60031.3171912936 \tabularnewline
213 & 4014972 & 4259497.44146325 & -244525.441463255 \tabularnewline
214 & 3983758 & 4176722.48940132 & -192964.489401320 \tabularnewline
215 & 3158459 & 3477811.93092676 & -319352.930926759 \tabularnewline
216 & 3100569 & 3372445.92597249 & -271876.925972493 \tabularnewline
217 & 2935404 & 3325486.87168998 & -390082.871689984 \tabularnewline
218 & 2855719 & 3243583.24659193 & -387864.246591928 \tabularnewline
219 & 3465611 & 3705081.46359913 & -239470.463599135 \tabularnewline
220 & 3006985 & 3841148.31218529 & -834163.312185289 \tabularnewline
221 & 4095110 & 4199484.89761355 & -104374.897613548 \tabularnewline
222 & 4104793 & 4194821.53567339 & -90028.5356733855 \tabularnewline
223 & 4730788 & 4637707.17373322 & 93080.8262667766 \tabularnewline
224 & 4642726 & 4614301.86442464 & 28424.1355753594 \tabularnewline
225 & 4246919 & 4329028.9886966 & -82109.9886966021 \tabularnewline
226 & 4308117 & 4246254.03663467 & 61862.9633653331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&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]1149822[/C][C]816261.8879084[/C][C]333560.112091599[/C][/ROW]
[ROW][C]2[/C][C]1086979[/C][C]746494.050496626[/C][C]340484.949503374[/C][/ROW]
[ROW][C]3[/C][C]1276674[/C][C]1220128.05519015[/C][C]56545.9448098508[/C][/ROW]
[ROW][C]4[/C][C]1522522[/C][C]1368330.69146261[/C][C]154191.308537389[/C][/ROW]
[ROW][C]5[/C][C]1742117[/C][C]1738803.06457718[/C][C]3313.93542282109[/C][/ROW]
[ROW][C]6[/C][C]1737275[/C][C]1746275.49032332[/C][C]-9000.49032332417[/C][/ROW]
[ROW][C]7[/C][C]1979900[/C][C]2201296.91606947[/C][C]-221396.916069471[/C][/ROW]
[ROW][C]8[/C][C]2061036[/C][C]2190027.39444719[/C][C]-128991.394447193[/C][/ROW]
[ROW][C]9[/C][C]1867943[/C][C]1916890.30640546[/C][C]-48947.3064054626[/C][/ROW]
[ROW][C]10[/C][C]1707752[/C][C]1846251.14202983[/C][C]-138499.142029834[/C][/ROW]
[ROW][C]11[/C][C]1298756[/C][C]1159476.37124158[/C][C]139279.628758419[/C][/ROW]
[ROW][C]12[/C][C]1281814[/C][C]1066246.15397362[/C][C]215567.846026375[/C][/ROW]
[ROW][C]13[/C][C]1281151[/C][C]1031422.88737742[/C][C]249728.112622576[/C][/ROW]
[ROW][C]14[/C][C]1164976[/C][C]961655.049965678[/C][C]203320.950034322[/C][/ROW]
[ROW][C]15[/C][C]1454329[/C][C]1435289.05465919[/C][C]19039.9453408111[/C][/ROW]
[ROW][C]16[/C][C]1645288[/C][C]1583491.69093165[/C][C]61796.3090683493[/C][/ROW]
[ROW][C]17[/C][C]1817743[/C][C]1953964.06404622[/C][C]-136221.064046218[/C][/ROW]
[ROW][C]18[/C][C]1895785[/C][C]1961436.48979236[/C][C]-65651.4897923634[/C][/ROW]
[ROW][C]19[/C][C]2236311[/C][C]2416457.91553851[/C][C]-180146.915538509[/C][/ROW]
[ROW][C]20[/C][C]2295951[/C][C]2405188.39391623[/C][C]-109237.393916234[/C][/ROW]
[ROW][C]21[/C][C]2087315[/C][C]2132051.30587450[/C][C]-44736.3058745028[/C][/ROW]
[ROW][C]22[/C][C]1980891[/C][C]2061412.14149888[/C][C]-80521.1414988753[/C][/ROW]
[ROW][C]23[/C][C]1465446[/C][C]1374637.37071062[/C][C]90808.6292893783[/C][/ROW]
[ROW][C]24[/C][C]1445026[/C][C]1281407.15344266[/C][C]163618.846557336[/C][/ROW]
[ROW][C]25[/C][C]1488120[/C][C]1246583.88684646[/C][C]241536.113153537[/C][/ROW]
[ROW][C]26[/C][C]1338333[/C][C]1176816.04943472[/C][C]161516.950565285[/C][/ROW]
[ROW][C]27[/C][C]1715789[/C][C]1650450.05412823[/C][C]65338.9458717712[/C][/ROW]
[ROW][C]28[/C][C]1806090[/C][C]1798652.69040069[/C][C]7437.30959930965[/C][/ROW]
[ROW][C]29[/C][C]2083316[/C][C]2169125.06351526[/C][C]-85809.063515257[/C][/ROW]
[ROW][C]30[/C][C]2092278[/C][C]2176597.48926140[/C][C]-84319.4892614029[/C][/ROW]
[ROW][C]31[/C][C]2430800[/C][C]2631618.91500755[/C][C]-200818.915007549[/C][/ROW]
[ROW][C]32[/C][C]2424894[/C][C]2620349.39338527[/C][C]-195455.393385274[/C][/ROW]
[ROW][C]33[/C][C]2299016[/C][C]2347212.30534354[/C][C]-48196.3053435425[/C][/ROW]
[ROW][C]34[/C][C]2130688[/C][C]2276573.14096791[/C][C]-145885.140967915[/C][/ROW]
[ROW][C]35[/C][C]1652221[/C][C]1589798.37017966[/C][C]62422.6298203386[/C][/ROW]
[ROW][C]36[/C][C]1608162[/C][C]1496568.15291170[/C][C]111593.847088296[/C][/ROW]
[ROW][C]37[/C][C]1647074[/C][C]1461744.88631550[/C][C]185329.113684498[/C][/ROW]
[ROW][C]38[/C][C]1479691[/C][C]1391977.04890375[/C][C]87713.951096245[/C][/ROW]
[ROW][C]39[/C][C]1884978[/C][C]1865611.05359727[/C][C]19366.9464027316[/C][/ROW]
[ROW][C]40[/C][C]2007898[/C][C]2013813.68986973[/C][C]-5915.68986973007[/C][/ROW]
[ROW][C]41[/C][C]2208954[/C][C]2384286.0629843[/C][C]-175332.062984297[/C][/ROW]
[ROW][C]42[/C][C]2217164[/C][C]2391758.48873044[/C][C]-174594.488730443[/C][/ROW]
[ROW][C]43[/C][C]2534291[/C][C]2846779.91447659[/C][C]-312488.914476588[/C][/ROW]
[ROW][C]44[/C][C]2560312[/C][C]2835510.39285431[/C][C]-275198.392854313[/C][/ROW]
[ROW][C]45[/C][C]2429069[/C][C]2562373.30481258[/C][C]-133304.304812582[/C][/ROW]
[ROW][C]46[/C][C]2315077[/C][C]2491734.14043695[/C][C]-176657.140436955[/C][/ROW]
[ROW][C]47[/C][C]1799608[/C][C]1804959.3696487[/C][C]-5351.3696487012[/C][/ROW]
[ROW][C]48[/C][C]1772590[/C][C]1711729.15238074[/C][C]60860.8476192564[/C][/ROW]
[ROW][C]49[/C][C]1744799[/C][C]1676905.88578454[/C][C]67893.1142154581[/C][/ROW]
[ROW][C]50[/C][C]1659093[/C][C]1607138.04837279[/C][C]51954.9516272056[/C][/ROW]
[ROW][C]51[/C][C]2099821[/C][C]2080772.05306631[/C][C]19048.9469336920[/C][/ROW]
[ROW][C]52[/C][C]2135736[/C][C]2228974.68933877[/C][C]-93238.6893387697[/C][/ROW]
[ROW][C]53[/C][C]2427894[/C][C]2599447.06245334[/C][C]-171553.062453337[/C][/ROW]
[ROW][C]54[/C][C]2468882[/C][C]2606919.48819948[/C][C]-138037.488199482[/C][/ROW]
[ROW][C]55[/C][C]2703217[/C][C]3061940.91394563[/C][C]-358723.913945628[/C][/ROW]
[ROW][C]56[/C][C]2766841[/C][C]3050671.39232335[/C][C]-283830.392323352[/C][/ROW]
[ROW][C]57[/C][C]2655236[/C][C]2777534.30428162[/C][C]-122298.304281622[/C][/ROW]
[ROW][C]58[/C][C]2550373[/C][C]2706895.13990599[/C][C]-156522.139905994[/C][/ROW]
[ROW][C]59[/C][C]2052097[/C][C]2020120.36911774[/C][C]31976.6308822592[/C][/ROW]
[ROW][C]60[/C][C]1998055[/C][C]1926890.15184978[/C][C]71164.8481502167[/C][/ROW]
[ROW][C]61[/C][C]1920748[/C][C]1892066.88525358[/C][C]28681.1147464185[/C][/ROW]
[ROW][C]62[/C][C]1876694[/C][C]1822299.04784183[/C][C]54394.9521581658[/C][/ROW]
[ROW][C]63[/C][C]2380930[/C][C]2295933.05253535[/C][C]84996.9474646523[/C][/ROW]
[ROW][C]64[/C][C]2467402[/C][C]2444135.68880781[/C][C]23266.3111921906[/C][/ROW]
[ROW][C]65[/C][C]2770771[/C][C]2814608.06192238[/C][C]-43837.061922376[/C][/ROW]
[ROW][C]66[/C][C]2781340[/C][C]2822080.48766852[/C][C]-40740.4876685219[/C][/ROW]
[ROW][C]67[/C][C]3143926[/C][C]3277101.91341467[/C][C]-133175.913414667[/C][/ROW]
[ROW][C]68[/C][C]3172235[/C][C]3265832.39179239[/C][C]-93597.3917923924[/C][/ROW]
[ROW][C]69[/C][C]2952540[/C][C]2992695.30375066[/C][C]-40155.3037506614[/C][/ROW]
[ROW][C]70[/C][C]2920877[/C][C]2922056.13937503[/C][C]-1179.13937503405[/C][/ROW]
[ROW][C]71[/C][C]2384552[/C][C]2235281.36858678[/C][C]149270.631413220[/C][/ROW]
[ROW][C]72[/C][C]2248987[/C][C]2142051.15131882[/C][C]106935.848681177[/C][/ROW]
[ROW][C]73[/C][C]2208616[/C][C]2107227.88472262[/C][C]101388.115277379[/C][/ROW]
[ROW][C]74[/C][C]2178756[/C][C]2037460.04731087[/C][C]141295.952689126[/C][/ROW]
[ROW][C]75[/C][C]2632870[/C][C]2511094.05200439[/C][C]121775.947995613[/C][/ROW]
[ROW][C]76[/C][C]2706905[/C][C]2659296.68827685[/C][C]47608.311723151[/C][/ROW]
[ROW][C]77[/C][C]3029745[/C][C]3029769.06139142[/C][C]-24.0613914158566[/C][/ROW]
[ROW][C]78[/C][C]3015402[/C][C]3037241.48713756[/C][C]-21839.4871375617[/C][/ROW]
[ROW][C]79[/C][C]3391414[/C][C]3492262.91288371[/C][C]-100848.912883707[/C][/ROW]
[ROW][C]80[/C][C]3507805[/C][C]3480993.39126143[/C][C]26811.6087385679[/C][/ROW]
[ROW][C]81[/C][C]3177852[/C][C]3207856.3032197[/C][C]-30004.3032197012[/C][/ROW]
[ROW][C]82[/C][C]3142961[/C][C]3137217.13884407[/C][C]5743.86115592631[/C][/ROW]
[ROW][C]83[/C][C]2545815[/C][C]2450442.36805582[/C][C]95372.63194418[/C][/ROW]
[ROW][C]84[/C][C]2414007[/C][C]2357212.15078786[/C][C]56794.8492121372[/C][/ROW]
[ROW][C]85[/C][C]2372578[/C][C]2322388.88419166[/C][C]50189.1158083391[/C][/ROW]
[ROW][C]86[/C][C]2332664[/C][C]2252621.04677991[/C][C]80042.9532200866[/C][/ROW]
[ROW][C]87[/C][C]2825328[/C][C]2726255.05147343[/C][C]99072.948526573[/C][/ROW]
[ROW][C]88[/C][C]2901478[/C][C]2874457.68774589[/C][C]27020.3122541113[/C][/ROW]
[ROW][C]89[/C][C]3263955[/C][C]3244930.06086046[/C][C]19024.9391395444[/C][/ROW]
[ROW][C]90[/C][C]3226738[/C][C]3252402.4866066[/C][C]-25664.4866066013[/C][/ROW]
[ROW][C]91[/C][C]3610786[/C][C]3707423.91235275[/C][C]-96637.9123527469[/C][/ROW]
[ROW][C]92[/C][C]3709274[/C][C]3696154.39073047[/C][C]13119.6092695282[/C][/ROW]
[ROW][C]93[/C][C]3467185[/C][C]3423017.30268874[/C][C]44167.6973112593[/C][/ROW]
[ROW][C]94[/C][C]3449646[/C][C]3352378.13831311[/C][C]97267.8616868867[/C][/ROW]
[ROW][C]95[/C][C]2802951[/C][C]2665603.36752486[/C][C]137347.632475141[/C][/ROW]
[ROW][C]96[/C][C]2462530[/C][C]2572373.1502569[/C][C]-109843.150256902[/C][/ROW]
[ROW][C]97[/C][C]2490645[/C][C]2537549.8836607[/C][C]-46904.8836607006[/C][/ROW]
[ROW][C]98[/C][C]2561520[/C][C]2467782.04624895[/C][C]93737.953751047[/C][/ROW]
[ROW][C]99[/C][C]3067554[/C][C]2941416.05094247[/C][C]126137.949057533[/C][/ROW]
[ROW][C]100[/C][C]3226951[/C][C]3089618.68721493[/C][C]137332.312785072[/C][/ROW]
[ROW][C]101[/C][C]3546493[/C][C]3460091.06032949[/C][C]86401.939670505[/C][/ROW]
[ROW][C]102[/C][C]3492787[/C][C]3467563.48607564[/C][C]25223.5139243592[/C][/ROW]
[ROW][C]103[/C][C]3952263[/C][C]3922584.91182179[/C][C]29678.0881782135[/C][/ROW]
[ROW][C]104[/C][C]3932072[/C][C]3911315.39019951[/C][C]20756.6098004885[/C][/ROW]
[ROW][C]105[/C][C]3720284[/C][C]3638178.30215778[/C][C]82105.6978422197[/C][/ROW]
[ROW][C]106[/C][C]3651555[/C][C]3567539.13778215[/C][C]84015.8622178469[/C][/ROW]
[ROW][C]107[/C][C]2914972[/C][C]2880764.3669939[/C][C]34207.6330061006[/C][/ROW]
[ROW][C]108[/C][C]2713514[/C][C]2787534.14972594[/C][C]-74020.149725942[/C][/ROW]
[ROW][C]109[/C][C]2703997[/C][C]2752710.88312974[/C][C]-48713.8831297401[/C][/ROW]
[ROW][C]110[/C][C]2591373[/C][C]2682943.04571799[/C][C]-91570.0457179927[/C][/ROW]
[ROW][C]111[/C][C]3163748[/C][C]3156577.05041151[/C][C]7170.9495884936[/C][/ROW]
[ROW][C]112[/C][C]3355137[/C][C]3304779.68668397[/C][C]50357.313316032[/C][/ROW]
[ROW][C]113[/C][C]3613702[/C][C]3675252.05979853[/C][C]-61550.0597985347[/C][/ROW]
[ROW][C]114[/C][C]3686773[/C][C]3682724.48554468[/C][C]4048.51445531931[/C][/ROW]
[ROW][C]115[/C][C]4098716[/C][C]4137745.91129083[/C][C]-39029.9112908264[/C][/ROW]
[ROW][C]116[/C][C]4063517[/C][C]4126476.38966855[/C][C]-62959.3896685509[/C][/ROW]
[ROW][C]117[/C][C]3551489[/C][C]3703245.06359648[/C][C]-151756.063596479[/C][/ROW]
[ROW][C]118[/C][C]3226663[/C][C]3620470.11153454[/C][C]-393807.111534544[/C][/ROW]
[ROW][C]119[/C][C]2656842[/C][C]2921559.55305998[/C][C]-264717.553059982[/C][/ROW]
[ROW][C]120[/C][C]2597484[/C][C]2816193.54810572[/C][C]-218709.548105718[/C][/ROW]
[ROW][C]121[/C][C]2572399[/C][C]2769234.49382321[/C][C]-196835.493823208[/C][/ROW]
[ROW][C]122[/C][C]2596631[/C][C]2687330.86872515[/C][C]-90699.8687251525[/C][/ROW]
[ROW][C]123[/C][C]3165225[/C][C]3148829.08573236[/C][C]16395.9142676415[/C][/ROW]
[ROW][C]124[/C][C]3303145[/C][C]3284895.93431851[/C][C]18249.0656814877[/C][/ROW]
[ROW][C]125[/C][C]3698247[/C][C]3643232.51974677[/C][C]55014.4802532287[/C][/ROW]
[ROW][C]126[/C][C]3668631[/C][C]3638569.15780661[/C][C]30061.8421933905[/C][/ROW]
[ROW][C]127[/C][C]4130433[/C][C]4081454.79586645[/C][C]48978.2041335522[/C][/ROW]
[ROW][C]128[/C][C]4131400[/C][C]4058049.48655786[/C][C]73350.5134421357[/C][/ROW]
[ROW][C]129[/C][C]3864358[/C][C]3772776.61082983[/C][C]91581.3891701742[/C][/ROW]
[ROW][C]130[/C][C]3721110[/C][C]3690001.65876789[/C][C]31108.3412321093[/C][/ROW]
[ROW][C]131[/C][C]2892532[/C][C]2991091.10029333[/C][C]-98559.1002933295[/C][/ROW]
[ROW][C]132[/C][C]2843451[/C][C]2885725.09533906[/C][C]-42274.0953390645[/C][/ROW]
[ROW][C]133[/C][C]2747502[/C][C]2838766.04105655[/C][C]-91264.0410565549[/C][/ROW]
[ROW][C]134[/C][C]2668775[/C][C]2756862.4159585[/C][C]-88087.4159584995[/C][/ROW]
[ROW][C]135[/C][C]3018602[/C][C]3218360.63296571[/C][C]-199758.632965706[/C][/ROW]
[ROW][C]136[/C][C]3013392[/C][C]3354427.48155186[/C][C]-341035.481551859[/C][/ROW]
[ROW][C]137[/C][C]3393657[/C][C]3712764.06698012[/C][C]-319107.066980118[/C][/ROW]
[ROW][C]138[/C][C]3544233[/C][C]3708100.70503996[/C][C]-163867.705039957[/C][/ROW]
[ROW][C]139[/C][C]4075832[/C][C]4150986.34309979[/C][C]-75154.3430997945[/C][/ROW]
[ROW][C]140[/C][C]4032923[/C][C]4127581.03379121[/C][C]-94658.0337912118[/C][/ROW]
[ROW][C]141[/C][C]3734509[/C][C]3842308.15806317[/C][C]-107799.158063173[/C][/ROW]
[ROW][C]142[/C][C]3761285[/C][C]3759533.20600124[/C][C]1751.79399876225[/C][/ROW]
[ROW][C]143[/C][C]2970090[/C][C]3060622.64752668[/C][C]-90532.6475266765[/C][/ROW]
[ROW][C]144[/C][C]2847849[/C][C]2955256.64257241[/C][C]-107407.642572411[/C][/ROW]
[ROW][C]145[/C][C]2741680[/C][C]2908297.5882899[/C][C]-166617.588289902[/C][/ROW]
[ROW][C]146[/C][C]2830639[/C][C]2826393.96319185[/C][C]4245.03680815336[/C][/ROW]
[ROW][C]147[/C][C]3257673[/C][C]3287892.18019905[/C][C]-30219.1801990526[/C][/ROW]
[ROW][C]148[/C][C]3480085[/C][C]3423959.02878521[/C][C]56125.9712147934[/C][/ROW]
[ROW][C]149[/C][C]3843271[/C][C]3782295.61421347[/C][C]60975.3857865343[/C][/ROW]
[ROW][C]150[/C][C]3796961[/C][C]3777632.2522733[/C][C]19328.7477266964[/C][/ROW]
[ROW][C]151[/C][C]4337767[/C][C]4220517.89033314[/C][C]117249.109666859[/C][/ROW]
[ROW][C]152[/C][C]4243630[/C][C]4197112.58102456[/C][C]46517.4189754411[/C][/ROW]
[ROW][C]153[/C][C]3927202[/C][C]3911839.70529652[/C][C]15362.2947034800[/C][/ROW]
[ROW][C]154[/C][C]3915296[/C][C]3829064.75323458[/C][C]86231.2467654155[/C][/ROW]
[ROW][C]155[/C][C]3087396[/C][C]3130154.19476002[/C][C]-42758.1947600235[/C][/ROW]
[ROW][C]156[/C][C]2963792[/C][C]3024788.18980576[/C][C]-60996.1898057584[/C][/ROW]
[ROW][C]157[/C][C]2955792[/C][C]2977829.13552325[/C][C]-22037.1355232488[/C][/ROW]
[ROW][C]158[/C][C]2829925[/C][C]2895925.51042519[/C][C]-66000.5104251937[/C][/ROW]
[ROW][C]159[/C][C]3281195[/C][C]3357423.7274324[/C][C]-76228.7274323997[/C][/ROW]
[ROW][C]160[/C][C]3548011[/C][C]3493490.57601855[/C][C]54520.4239814465[/C][/ROW]
[ROW][C]161[/C][C]4059648[/C][C]3851827.16144681[/C][C]207820.838553187[/C][/ROW]
[ROW][C]162[/C][C]3941175[/C][C]3847163.79950665[/C][C]94011.2004933491[/C][/ROW]
[ROW][C]163[/C][C]4528594[/C][C]4290049.43756649[/C][C]238544.562433511[/C][/ROW]
[ROW][C]164[/C][C]4433151[/C][C]4266644.12825791[/C][C]166506.871742094[/C][/ROW]
[ROW][C]165[/C][C]4145737[/C][C]3981371.25252987[/C][C]164365.747470133[/C][/ROW]
[ROW][C]166[/C][C]4077132[/C][C]3898596.30046793[/C][C]178535.699532068[/C][/ROW]
[ROW][C]167[/C][C]3198519[/C][C]3199685.74199337[/C][C]-1166.74199337055[/C][/ROW]
[ROW][C]168[/C][C]3078660[/C][C]3094319.73703911[/C][C]-15659.7370391055[/C][/ROW]
[ROW][C]169[/C][C]3028202[/C][C]3047360.68275660[/C][C]-19158.6827565959[/C][/ROW]
[ROW][C]170[/C][C]2858642[/C][C]2965457.05765854[/C][C]-106815.057658541[/C][/ROW]
[ROW][C]171[/C][C]3398954[/C][C]3426955.27466575[/C][C]-28001.2746657467[/C][/ROW]
[ROW][C]172[/C][C]3808883[/C][C]3563022.1232519[/C][C]245860.876748099[/C][/ROW]
[ROW][C]173[/C][C]4175961[/C][C]3921358.70868016[/C][C]254602.291319841[/C][/ROW]
[ROW][C]174[/C][C]4227542[/C][C]3916695.34674[/C][C]310846.653260002[/C][/ROW]
[ROW][C]175[/C][C]4744616[/C][C]4359580.98479984[/C][C]385035.015200164[/C][/ROW]
[ROW][C]176[/C][C]4608012[/C][C]4336175.67549125[/C][C]271836.324508747[/C][/ROW]
[ROW][C]177[/C][C]4295049[/C][C]4050902.79976321[/C][C]244146.200236786[/C][/ROW]
[ROW][C]178[/C][C]4201144[/C][C]3968127.84770128[/C][C]233016.152298721[/C][/ROW]
[ROW][C]179[/C][C]3353276[/C][C]3269217.28922672[/C][C]84058.7107732822[/C][/ROW]
[ROW][C]180[/C][C]3286851[/C][C]3163851.28427245[/C][C]122999.715727548[/C][/ROW]
[ROW][C]181[/C][C]3169889[/C][C]3116892.22998994[/C][C]52996.770010057[/C][/ROW]
[ROW][C]182[/C][C]3051720[/C][C]3034988.60489189[/C][C]16731.3951081122[/C][/ROW]
[ROW][C]183[/C][C]3695426[/C][C]3496486.82189909[/C][C]198939.178100906[/C][/ROW]
[ROW][C]184[/C][C]3905501[/C][C]3632553.67048525[/C][C]272947.329514752[/C][/ROW]
[ROW][C]185[/C][C]4296458[/C][C]3990890.25591351[/C][C]305567.744086493[/C][/ROW]
[ROW][C]186[/C][C]4246247[/C][C]3986226.89397334[/C][C]260020.106026655[/C][/ROW]
[ROW][C]187[/C][C]4921849[/C][C]4429112.53203318[/C][C]492736.467966817[/C][/ROW]
[ROW][C]188[/C][C]4821446[/C][C]4405707.2227246[/C][C]415738.7772754[/C][/ROW]
[ROW][C]189[/C][C]4425064[/C][C]4120434.34699656[/C][C]304629.653003439[/C][/ROW]
[ROW][C]190[/C][C]4379099[/C][C]4037659.39493463[/C][C]341439.605065374[/C][/ROW]
[ROW][C]191[/C][C]3472889[/C][C]3338748.83646006[/C][C]134140.163539935[/C][/ROW]
[ROW][C]192[/C][C]3359160[/C][C]3233382.8315058[/C][C]125777.168494201[/C][/ROW]
[ROW][C]193[/C][C]3200944[/C][C]3186423.77722329[/C][C]14520.2227767100[/C][/ROW]
[ROW][C]194[/C][C]3153170[/C][C]3104520.15212523[/C][C]48649.8478747652[/C][/ROW]
[ROW][C]195[/C][C]3741498[/C][C]3566018.36913244[/C][C]175479.630867559[/C][/ROW]
[ROW][C]196[/C][C]3918719[/C][C]3702085.21771859[/C][C]216633.782281405[/C][/ROW]
[ROW][C]197[/C][C]4403449[/C][C]4060421.80314685[/C][C]343027.196853146[/C][/ROW]
[ROW][C]198[/C][C]4400407[/C][C]4055758.44120669[/C][C]344648.558793308[/C][/ROW]
[ROW][C]199[/C][C]4847473[/C][C]4498644.07926653[/C][C]348828.92073347[/C][/ROW]
[ROW][C]200[/C][C]4716136[/C][C]4475238.76995795[/C][C]240897.230042053[/C][/ROW]
[ROW][C]201[/C][C]4297440[/C][C]4189965.89422991[/C][C]107474.105770092[/C][/ROW]
[ROW][C]202[/C][C]4272253[/C][C]4107190.94216797[/C][C]165062.057832027[/C][/ROW]
[ROW][C]203[/C][C]3271834[/C][C]3408280.38369341[/C][C]-136446.383693411[/C][/ROW]
[ROW][C]204[/C][C]3168388[/C][C]3302914.37873915[/C][C]-134526.378739147[/C][/ROW]
[ROW][C]205[/C][C]2911748[/C][C]3255955.32445664[/C][C]-344207.324456637[/C][/ROW]
[ROW][C]206[/C][C]2720999[/C][C]3174051.69935858[/C][C]-453052.699358582[/C][/ROW]
[ROW][C]207[/C][C]3199918[/C][C]3635549.91636579[/C][C]-435631.916365788[/C][/ROW]
[ROW][C]208[/C][C]3672623[/C][C]3771616.76495194[/C][C]-98993.7649519414[/C][/ROW]
[ROW][C]209[/C][C]3892013[/C][C]4129953.3503802[/C][C]-237940.350380200[/C][/ROW]
[ROW][C]210[/C][C]3850845[/C][C]4125289.98844004[/C][C]-274444.988440038[/C][/ROW]
[ROW][C]211[/C][C]4532467[/C][C]4568175.62649988[/C][C]-35708.6264998764[/C][/ROW]
[ROW][C]212[/C][C]4484739[/C][C]4544770.31719129[/C][C]-60031.3171912936[/C][/ROW]
[ROW][C]213[/C][C]4014972[/C][C]4259497.44146325[/C][C]-244525.441463255[/C][/ROW]
[ROW][C]214[/C][C]3983758[/C][C]4176722.48940132[/C][C]-192964.489401320[/C][/ROW]
[ROW][C]215[/C][C]3158459[/C][C]3477811.93092676[/C][C]-319352.930926759[/C][/ROW]
[ROW][C]216[/C][C]3100569[/C][C]3372445.92597249[/C][C]-271876.925972493[/C][/ROW]
[ROW][C]217[/C][C]2935404[/C][C]3325486.87168998[/C][C]-390082.871689984[/C][/ROW]
[ROW][C]218[/C][C]2855719[/C][C]3243583.24659193[/C][C]-387864.246591928[/C][/ROW]
[ROW][C]219[/C][C]3465611[/C][C]3705081.46359913[/C][C]-239470.463599135[/C][/ROW]
[ROW][C]220[/C][C]3006985[/C][C]3841148.31218529[/C][C]-834163.312185289[/C][/ROW]
[ROW][C]221[/C][C]4095110[/C][C]4199484.89761355[/C][C]-104374.897613548[/C][/ROW]
[ROW][C]222[/C][C]4104793[/C][C]4194821.53567339[/C][C]-90028.5356733855[/C][/ROW]
[ROW][C]223[/C][C]4730788[/C][C]4637707.17373322[/C][C]93080.8262667766[/C][/ROW]
[ROW][C]224[/C][C]4642726[/C][C]4614301.86442464[/C][C]28424.1355753594[/C][/ROW]
[ROW][C]225[/C][C]4246919[/C][C]4329028.9886966[/C][C]-82109.9886966021[/C][/ROW]
[ROW][C]226[/C][C]4308117[/C][C]4246254.03663467[/C][C]61862.9633653331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11149822816261.8879084333560.112091599
21086979746494.050496626340484.949503374
312766741220128.0551901556545.9448098508
415225221368330.69146261154191.308537389
517421171738803.064577183313.93542282109
617372751746275.49032332-9000.49032332417
719799002201296.91606947-221396.916069471
820610362190027.39444719-128991.394447193
918679431916890.30640546-48947.3064054626
1017077521846251.14202983-138499.142029834
1112987561159476.37124158139279.628758419
1212818141066246.15397362215567.846026375
1312811511031422.88737742249728.112622576
141164976961655.049965678203320.950034322
1514543291435289.0546591919039.9453408111
1616452881583491.6909316561796.3090683493
1718177431953964.06404622-136221.064046218
1818957851961436.48979236-65651.4897923634
1922363112416457.91553851-180146.915538509
2022959512405188.39391623-109237.393916234
2120873152132051.30587450-44736.3058745028
2219808912061412.14149888-80521.1414988753
2314654461374637.3707106290808.6292893783
2414450261281407.15344266163618.846557336
2514881201246583.88684646241536.113153537
2613383331176816.04943472161516.950565285
2717157891650450.0541282365338.9458717712
2818060901798652.690400697437.30959930965
2920833162169125.06351526-85809.063515257
3020922782176597.48926140-84319.4892614029
3124308002631618.91500755-200818.915007549
3224248942620349.39338527-195455.393385274
3322990162347212.30534354-48196.3053435425
3421306882276573.14096791-145885.140967915
3516522211589798.3701796662422.6298203386
3616081621496568.15291170111593.847088296
3716470741461744.88631550185329.113684498
3814796911391977.0489037587713.951096245
3918849781865611.0535972719366.9464027316
4020078982013813.68986973-5915.68986973007
4122089542384286.0629843-175332.062984297
4222171642391758.48873044-174594.488730443
4325342912846779.91447659-312488.914476588
4425603122835510.39285431-275198.392854313
4524290692562373.30481258-133304.304812582
4623150772491734.14043695-176657.140436955
4717996081804959.3696487-5351.3696487012
4817725901711729.1523807460860.8476192564
4917447991676905.8857845467893.1142154581
5016590931607138.0483727951954.9516272056
5120998212080772.0530663119048.9469336920
5221357362228974.68933877-93238.6893387697
5324278942599447.06245334-171553.062453337
5424688822606919.48819948-138037.488199482
5527032173061940.91394563-358723.913945628
5627668413050671.39232335-283830.392323352
5726552362777534.30428162-122298.304281622
5825503732706895.13990599-156522.139905994
5920520972020120.3691177431976.6308822592
6019980551926890.1518497871164.8481502167
6119207481892066.8852535828681.1147464185
6218766941822299.0478418354394.9521581658
6323809302295933.0525353584996.9474646523
6424674022444135.6888078123266.3111921906
6527707712814608.06192238-43837.061922376
6627813402822080.48766852-40740.4876685219
6731439263277101.91341467-133175.913414667
6831722353265832.39179239-93597.3917923924
6929525402992695.30375066-40155.3037506614
7029208772922056.13937503-1179.13937503405
7123845522235281.36858678149270.631413220
7222489872142051.15131882106935.848681177
7322086162107227.88472262101388.115277379
7421787562037460.04731087141295.952689126
7526328702511094.05200439121775.947995613
7627069052659296.6882768547608.311723151
7730297453029769.06139142-24.0613914158566
7830154023037241.48713756-21839.4871375617
7933914143492262.91288371-100848.912883707
8035078053480993.3912614326811.6087385679
8131778523207856.3032197-30004.3032197012
8231429613137217.138844075743.86115592631
8325458152450442.3680558295372.63194418
8424140072357212.1507878656794.8492121372
8523725782322388.8841916650189.1158083391
8623326642252621.0467799180042.9532200866
8728253282726255.0514734399072.948526573
8829014782874457.6877458927020.3122541113
8932639553244930.0608604619024.9391395444
9032267383252402.4866066-25664.4866066013
9136107863707423.91235275-96637.9123527469
9237092743696154.3907304713119.6092695282
9334671853423017.3026887444167.6973112593
9434496463352378.1383131197267.8616868867
9528029512665603.36752486137347.632475141
9624625302572373.1502569-109843.150256902
9724906452537549.8836607-46904.8836607006
9825615202467782.0462489593737.953751047
9930675542941416.05094247126137.949057533
10032269513089618.68721493137332.312785072
10135464933460091.0603294986401.939670505
10234927873467563.4860756425223.5139243592
10339522633922584.9118217929678.0881782135
10439320723911315.3901995120756.6098004885
10537202843638178.3021577882105.6978422197
10636515553567539.1377821584015.8622178469
10729149722880764.366993934207.6330061006
10827135142787534.14972594-74020.149725942
10927039972752710.88312974-48713.8831297401
11025913732682943.04571799-91570.0457179927
11131637483156577.050411517170.9495884936
11233551373304779.6866839750357.313316032
11336137023675252.05979853-61550.0597985347
11436867733682724.485544684048.51445531931
11540987164137745.91129083-39029.9112908264
11640635174126476.38966855-62959.3896685509
11735514893703245.06359648-151756.063596479
11832266633620470.11153454-393807.111534544
11926568422921559.55305998-264717.553059982
12025974842816193.54810572-218709.548105718
12125723992769234.49382321-196835.493823208
12225966312687330.86872515-90699.8687251525
12331652253148829.0857323616395.9142676415
12433031453284895.9343185118249.0656814877
12536982473643232.5197467755014.4802532287
12636686313638569.1578066130061.8421933905
12741304334081454.7958664548978.2041335522
12841314004058049.4865578673350.5134421357
12938643583772776.6108298391581.3891701742
13037211103690001.6587678931108.3412321093
13128925322991091.10029333-98559.1002933295
13228434512885725.09533906-42274.0953390645
13327475022838766.04105655-91264.0410565549
13426687752756862.4159585-88087.4159584995
13530186023218360.63296571-199758.632965706
13630133923354427.48155186-341035.481551859
13733936573712764.06698012-319107.066980118
13835442333708100.70503996-163867.705039957
13940758324150986.34309979-75154.3430997945
14040329234127581.03379121-94658.0337912118
14137345093842308.15806317-107799.158063173
14237612853759533.206001241751.79399876225
14329700903060622.64752668-90532.6475266765
14428478492955256.64257241-107407.642572411
14527416802908297.5882899-166617.588289902
14628306392826393.963191854245.03680815336
14732576733287892.18019905-30219.1801990526
14834800853423959.0287852156125.9712147934
14938432713782295.6142134760975.3857865343
15037969613777632.252273319328.7477266964
15143377674220517.89033314117249.109666859
15242436304197112.5810245646517.4189754411
15339272023911839.7052965215362.2947034800
15439152963829064.7532345886231.2467654155
15530873963130154.19476002-42758.1947600235
15629637923024788.18980576-60996.1898057584
15729557922977829.13552325-22037.1355232488
15828299252895925.51042519-66000.5104251937
15932811953357423.7274324-76228.7274323997
16035480113493490.5760185554520.4239814465
16140596483851827.16144681207820.838553187
16239411753847163.7995066594011.2004933491
16345285944290049.43756649238544.562433511
16444331514266644.12825791166506.871742094
16541457373981371.25252987164365.747470133
16640771323898596.30046793178535.699532068
16731985193199685.74199337-1166.74199337055
16830786603094319.73703911-15659.7370391055
16930282023047360.68275660-19158.6827565959
17028586422965457.05765854-106815.057658541
17133989543426955.27466575-28001.2746657467
17238088833563022.1232519245860.876748099
17341759613921358.70868016254602.291319841
17442275423916695.34674310846.653260002
17547446164359580.98479984385035.015200164
17646080124336175.67549125271836.324508747
17742950494050902.79976321244146.200236786
17842011443968127.84770128233016.152298721
17933532763269217.2892267284058.7107732822
18032868513163851.28427245122999.715727548
18131698893116892.2299899452996.770010057
18230517203034988.6048918916731.3951081122
18336954263496486.82189909198939.178100906
18439055013632553.67048525272947.329514752
18542964583990890.25591351305567.744086493
18642462473986226.89397334260020.106026655
18749218494429112.53203318492736.467966817
18848214464405707.2227246415738.7772754
18944250644120434.34699656304629.653003439
19043790994037659.39493463341439.605065374
19134728893338748.83646006134140.163539935
19233591603233382.8315058125777.168494201
19332009443186423.7772232914520.2227767100
19431531703104520.1521252348649.8478747652
19537414983566018.36913244175479.630867559
19639187193702085.21771859216633.782281405
19744034494060421.80314685343027.196853146
19844004074055758.44120669344648.558793308
19948474734498644.07926653348828.92073347
20047161364475238.76995795240897.230042053
20142974404189965.89422991107474.105770092
20242722534107190.94216797165062.057832027
20332718343408280.38369341-136446.383693411
20431683883302914.37873915-134526.378739147
20529117483255955.32445664-344207.324456637
20627209993174051.69935858-453052.699358582
20731999183635549.91636579-435631.916365788
20836726233771616.76495194-98993.7649519414
20938920134129953.3503802-237940.350380200
21038508454125289.98844004-274444.988440038
21145324674568175.62649988-35708.6264998764
21244847394544770.31719129-60031.3171912936
21340149724259497.44146325-244525.441463255
21439837584176722.48940132-192964.489401320
21531584593477811.93092676-319352.930926759
21631005693372445.92597249-271876.925972493
21729354043325486.87168998-390082.871689984
21828557193243583.24659193-387864.246591928
21934656113705081.46359913-239470.463599135
22030069853841148.31218529-834163.312185289
22140951104199484.89761355-104374.897613548
22241047934194821.53567339-90028.5356733855
22347307884637707.1737332293080.8262667766
22446427264614301.8644246428424.1355753594
22542469194329028.9886966-82109.9886966021
22643081174246254.0366346761862.9633653331







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
180.01223544324080820.02447088648161650.987764556759192
190.01460182756269550.02920365512539100.985398172437304
200.007021213280607350.01404242656121470.992978786719393
210.00257322210476790.00514644420953580.997426777895232
220.001675606934023650.003351213868047310.998324393065976
230.0004789497470366660.0009578994940733330.999521050252963
240.0001330752638991540.0002661505277983080.9998669247361
253.78976755697904e-057.57953511395807e-050.99996210232443
261.30367673116642e-052.60735346233283e-050.999986963232688
271.00845442344891e-052.01690884689783e-050.999989915455765
283.29626021688009e-066.59252043376018e-060.999996703739783
291.04569341416315e-062.09138682832631e-060.999998954306586
302.64087323432895e-075.28174646865791e-070.999999735912677
311.01618992792257e-072.03237985584515e-070.999999898381007
322.76997288697144e-085.53994577394287e-080.99999997230027
339.70075522821916e-091.94015104564383e-080.999999990299245
342.37595593097028e-094.75191186194057e-090.999999997624044
355.58575303035896e-101.11715060607179e-090.999999999441425
361.53669526402525e-103.07339052805049e-100.99999999984633
374.40128233857026e-118.80256467714051e-110.999999999955987
383.22811810582960e-116.45623621165921e-110.999999999967719
391.17060788176721e-112.34121576353442e-110.999999999988294
402.69404074882562e-125.38808149765123e-120.999999999997306
417.14080940462448e-131.42816188092490e-120.999999999999286
422.42305714623048e-134.84611429246095e-130.999999999999758
437.9722274520021e-141.59444549040042e-130.99999999999992
443.35724194015635e-146.7144838803127e-140.999999999999966
457.46287852060801e-151.49257570412160e-140.999999999999993
462.07155693867398e-154.14311387734796e-150.999999999999998
474.776713732852e-169.553427465704e-161
481.12240157060166e-162.24480314120331e-161
491.07140039870849e-162.14280079741698e-161
503.17136418486792e-176.34272836973584e-171
514.70535483396168e-179.41070966792336e-171
521.42936159091933e-172.85872318183867e-171
534.57013867308219e-189.14027734616439e-181
541.95605589310648e-183.91211178621295e-181
558.92617700819325e-191.78523540163865e-181
563.05258966150060e-196.10517932300119e-191
571.39944514369905e-192.79889028739810e-191
581.72464097794075e-193.44928195588149e-191
598.40808303232644e-201.68161660646529e-191
602.37348581048276e-204.74697162096552e-201
611.60824509322563e-203.21649018645125e-201
623.78243175135656e-217.56486350271313e-211
632.12533631081681e-194.25067262163362e-191
643.80346951377141e-197.60693902754282e-191
658.56304048513556e-181.71260809702711e-171
664.23808072281062e-178.47616144562125e-171
672.00442969784723e-154.00885939569446e-150.999999999999998
681.78616379756754e-143.57232759513508e-140.999999999999982
691.8965841185248e-143.7931682370496e-140.99999999999998
701.78188084897448e-133.56376169794897e-130.999999999999822
712.94484472716513e-135.88968945433026e-130.999999999999706
721.26748504590027e-132.53497009180054e-130.999999999999873
735.3230453131443e-141.06460906262886e-130.999999999999947
742.85210546919010e-145.70421093838021e-140.999999999999971
754.27336770328254e-148.54673540656509e-140.999999999999957
762.43189248751815e-144.8637849750363e-140.999999999999976
774.36949362829882e-148.73898725659765e-140.999999999999956
783.70946047655363e-147.41892095310726e-140.999999999999963
791.33393701045964e-132.66787402091928e-130.999999999999867
801.42229965515658e-122.84459931031316e-120.999999999998578
818.42132319830315e-131.68426463966063e-120.999999999999158
821.13361587130153e-122.26723174260306e-120.999999999998866
835.14545762706219e-131.02909152541244e-120.999999999999486
842.40445884284262e-134.80891768568524e-130.99999999999976
851.7262352601033e-133.4524705202066e-130.999999999999827
868.47076333903476e-141.69415266780695e-130.999999999999915
874.79401727094107e-149.58803454188215e-140.999999999999952
882.00763780660202e-144.01527561320404e-140.99999999999998
892.02296133366938e-144.04592266733876e-140.99999999999998
901.15141820603907e-142.30283641207814e-140.999999999999988
912.19225749858056e-144.38451499716112e-140.999999999999978
925.32896083186703e-141.06579216637341e-130.999999999999947
934.72273317372378e-149.44546634744756e-140.999999999999953
941.30452181753200e-132.60904363506399e-130.99999999999987
956.65209468115588e-141.33041893623118e-130.999999999999933
962.95898334328051e-135.91796668656101e-130.999999999999704
976.71889600726389e-131.34377920145278e-120.999999999999328
983.33121389980283e-136.66242779960566e-130.999999999999667
991.97780674055326e-133.95561348110652e-130.999999999999802
1001.65921781036832e-133.31843562073664e-130.999999999999834
1012.11624563176383e-134.23249126352766e-130.999999999999788
1021.35958359583488e-132.71916719166976e-130.999999999999864
1035.20307622889115e-131.04061524577823e-120.99999999999948
1046.20805589376538e-131.24161117875308e-120.99999999999938
1054.9437858827853e-139.8875717655706e-130.999999999999506
1064.83815006522327e-139.67630013044653e-130.999999999999516
1072.64650278502124e-135.29300557004248e-130.999999999999735
1083.89249591453678e-137.78499182907356e-130.99999999999961
1096.5963759864836e-131.31927519729672e-120.99999999999934
1101.80551768011680e-123.61103536023359e-120.999999999998195
1119.54811362085322e-131.90962272417064e-120.999999999999045
1124.74674401639808e-139.49348803279616e-130.999999999999525
1132.23185390792622e-134.46370781585244e-130.999999999999777
1141.20540600418994e-132.41081200837987e-130.99999999999988
1159.59336877342326e-141.91867375468465e-130.999999999999904
1164.61884065104327e-149.23768130208653e-140.999999999999954
1172.96682594854668e-145.93365189709337e-140.99999999999997
1181.04223138666480e-132.08446277332961e-130.999999999999896
1199.50967903739246e-141.90193580747849e-130.999999999999905
1209.5475346635977e-141.90950693271954e-130.999999999999905
1215.40388328782468e-141.08077665756494e-130.999999999999946
1224.05033679718842e-148.10067359437683e-140.99999999999996
1235.5707321599029e-141.11414643198058e-130.999999999999944
1243.63849524505239e-147.27699049010479e-140.999999999999964
1253.3053336048041e-146.6106672096082e-140.999999999999967
1261.63736700924160e-143.27473401848319e-140.999999999999984
1271.33610666292346e-142.67221332584693e-140.999999999999987
1286.60935313286634e-151.32187062657327e-140.999999999999993
1294.25992559212226e-158.51985118424451e-150.999999999999996
1303.77975009256245e-157.5595001851249e-150.999999999999996
1318.37442279490573e-141.67488455898115e-130.999999999999916
1321.90219792785771e-133.80439585571543e-130.99999999999981
1338.0227588862421e-131.60455177724842e-120.999999999999198
1341.69993624886529e-123.39987249773058e-120.9999999999983
1356.58622302312026e-121.31724460462405e-110.999999999993414
1361.32072683433539e-102.64145366867078e-100.999999999867927
1371.22641995495029e-092.45283990990058e-090.99999999877358
1381.95107568685006e-093.90215137370012e-090.999999998048924
1397.25717949984008e-091.45143589996802e-080.99999999274282
1401.55032084719504e-083.10064169439009e-080.999999984496792
1412.25789902030801e-084.51579804061602e-080.99999997742101
1423.25816426196389e-086.51632852392778e-080.999999967418357
1432.90280923171368e-085.80561846342736e-080.999999970971908
1442.94775996746386e-085.89551993492773e-080.9999999705224
1454.03697221245785e-088.0739444249157e-080.999999959630278
1462.26256948338941e-084.52513896677882e-080.999999977374305
1471.48306481412101e-082.96612962824201e-080.999999985169352
1481.08509180321529e-082.17018360643059e-080.999999989149082
1491.74001224656958e-083.48002449313917e-080.999999982599878
1502.42394274072340e-084.84788548144679e-080.999999975760573
1511.11506659574462e-072.23013319148924e-070.99999988849334
1522.61161362642186e-075.22322725284373e-070.999999738838637
1533.78163186232042e-077.56326372464085e-070.999999621836814
1546.16201653667139e-071.23240330733428e-060.999999383798346
1557.03562966720508e-071.40712593344102e-060.999999296437033
1561.00002580305371e-062.00005160610742e-060.999998999974197
1578.08677236035394e-071.61735447207079e-060.999999191322764
1588.00208492201118e-071.60041698440224e-060.999999199791508
1591.17507253018197e-062.35014506036394e-060.99999882492747
1609.42065418988267e-071.88413083797653e-060.999999057934581
1611.47419520981919e-062.94839041963838e-060.99999852580479
1622.53386343851803e-065.06772687703607e-060.999997466136561
1631.07326358467037e-052.14652716934074e-050.999989267364153
1642.66190733678372e-055.32381467356745e-050.999973380926632
1653.16882924828982e-056.33765849657964e-050.999968311707517
1665.50800759168271e-050.0001101601518336540.999944919924083
1677.72361789337881e-050.0001544723578675760.999922763821066
1680.0001417230062208230.0002834460124416460.99985827699378
1690.0001612568151259660.0003225136302519330.999838743184874
1700.0003338787590500450.000667757518100090.99966612124095
1710.000634541095924380.001269082191848760.999365458904076
1720.0004774301316564850.000954860263312970.999522569868344
1730.0005607072164861520.001121414432972300.999439292783514
1740.000592194458715660.001184388917431320.999407805541284
1750.001239280168574810.002478560337149620.998760719831425
1760.002159408503191080.004318817006382150.99784059149681
1770.002165172339089680.004330344678179350.99783482766091
1780.003624341204345220.007248682408690450.996375658795655
1790.003499859957772080.006999719915544170.996500140042228
1800.003049667081097520.006099334162195030.996950332918902
1810.00254491558479610.00508983116959220.997455084415204
1820.002318972364120720.004637944728241440.99768102763588
1830.001521218395541830.003042436791083670.998478781604458
1840.001221674539692590.002443349079385180.998778325460307
1850.0008892020397800040.001778404079560010.99911079796022
1860.0006603039909904890.001320607981980980.99933969600901
1870.0007155123409394940.001431024681878990.99928448765906
1880.0005655209697132270.001131041939426450.999434479030287
1890.0003440674121240370.0006881348242480740.999655932587876
1900.0002231206385411450.000446241277082290.99977687936146
1910.0001504598417605440.0003009196835210880.99984954015824
1929.63589849091027e-050.0001927179698182050.99990364101509
1938.78637575049426e-050.0001757275150098850.999912136242495
1949.67131993851262e-050.0001934263987702520.999903286800615
1950.0001133876459181500.0002267752918363010.999886612354082
1960.0007214156618651190.001442831323730240.999278584338135
1970.00147024615624990.00294049231249980.99852975384375
1980.004746848600312140.009493697200624280.995253151399688
1990.004806089464075440.009612178928150870.995193910535925
2000.003929144713402990.007858289426805990.996070855286597
2010.004382908317664470.008765816635328940.995617091682335
2020.004671701436424040.009343402872848080.995328298563576
2030.005842241136376790.01168448227275360.994157758863623
2040.005860349547564170.01172069909512830.994139650452436
2050.006606103970767420.01321220794153480.993393896029233
2060.007008286578867870.01401657315773570.992991713421132
2070.006827123115727770.01365424623145550.993172876884272
2080.9530431062277990.09391378754440280.0469568937722014

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 0.0122354432408082 & 0.0244708864816165 & 0.987764556759192 \tabularnewline
19 & 0.0146018275626955 & 0.0292036551253910 & 0.985398172437304 \tabularnewline
20 & 0.00702121328060735 & 0.0140424265612147 & 0.992978786719393 \tabularnewline
21 & 0.0025732221047679 & 0.0051464442095358 & 0.997426777895232 \tabularnewline
22 & 0.00167560693402365 & 0.00335121386804731 & 0.998324393065976 \tabularnewline
23 & 0.000478949747036666 & 0.000957899494073333 & 0.999521050252963 \tabularnewline
24 & 0.000133075263899154 & 0.000266150527798308 & 0.9998669247361 \tabularnewline
25 & 3.78976755697904e-05 & 7.57953511395807e-05 & 0.99996210232443 \tabularnewline
26 & 1.30367673116642e-05 & 2.60735346233283e-05 & 0.999986963232688 \tabularnewline
27 & 1.00845442344891e-05 & 2.01690884689783e-05 & 0.999989915455765 \tabularnewline
28 & 3.29626021688009e-06 & 6.59252043376018e-06 & 0.999996703739783 \tabularnewline
29 & 1.04569341416315e-06 & 2.09138682832631e-06 & 0.999998954306586 \tabularnewline
30 & 2.64087323432895e-07 & 5.28174646865791e-07 & 0.999999735912677 \tabularnewline
31 & 1.01618992792257e-07 & 2.03237985584515e-07 & 0.999999898381007 \tabularnewline
32 & 2.76997288697144e-08 & 5.53994577394287e-08 & 0.99999997230027 \tabularnewline
33 & 9.70075522821916e-09 & 1.94015104564383e-08 & 0.999999990299245 \tabularnewline
34 & 2.37595593097028e-09 & 4.75191186194057e-09 & 0.999999997624044 \tabularnewline
35 & 5.58575303035896e-10 & 1.11715060607179e-09 & 0.999999999441425 \tabularnewline
36 & 1.53669526402525e-10 & 3.07339052805049e-10 & 0.99999999984633 \tabularnewline
37 & 4.40128233857026e-11 & 8.80256467714051e-11 & 0.999999999955987 \tabularnewline
38 & 3.22811810582960e-11 & 6.45623621165921e-11 & 0.999999999967719 \tabularnewline
39 & 1.17060788176721e-11 & 2.34121576353442e-11 & 0.999999999988294 \tabularnewline
40 & 2.69404074882562e-12 & 5.38808149765123e-12 & 0.999999999997306 \tabularnewline
41 & 7.14080940462448e-13 & 1.42816188092490e-12 & 0.999999999999286 \tabularnewline
42 & 2.42305714623048e-13 & 4.84611429246095e-13 & 0.999999999999758 \tabularnewline
43 & 7.9722274520021e-14 & 1.59444549040042e-13 & 0.99999999999992 \tabularnewline
44 & 3.35724194015635e-14 & 6.7144838803127e-14 & 0.999999999999966 \tabularnewline
45 & 7.46287852060801e-15 & 1.49257570412160e-14 & 0.999999999999993 \tabularnewline
46 & 2.07155693867398e-15 & 4.14311387734796e-15 & 0.999999999999998 \tabularnewline
47 & 4.776713732852e-16 & 9.553427465704e-16 & 1 \tabularnewline
48 & 1.12240157060166e-16 & 2.24480314120331e-16 & 1 \tabularnewline
49 & 1.07140039870849e-16 & 2.14280079741698e-16 & 1 \tabularnewline
50 & 3.17136418486792e-17 & 6.34272836973584e-17 & 1 \tabularnewline
51 & 4.70535483396168e-17 & 9.41070966792336e-17 & 1 \tabularnewline
52 & 1.42936159091933e-17 & 2.85872318183867e-17 & 1 \tabularnewline
53 & 4.57013867308219e-18 & 9.14027734616439e-18 & 1 \tabularnewline
54 & 1.95605589310648e-18 & 3.91211178621295e-18 & 1 \tabularnewline
55 & 8.92617700819325e-19 & 1.78523540163865e-18 & 1 \tabularnewline
56 & 3.05258966150060e-19 & 6.10517932300119e-19 & 1 \tabularnewline
57 & 1.39944514369905e-19 & 2.79889028739810e-19 & 1 \tabularnewline
58 & 1.72464097794075e-19 & 3.44928195588149e-19 & 1 \tabularnewline
59 & 8.40808303232644e-20 & 1.68161660646529e-19 & 1 \tabularnewline
60 & 2.37348581048276e-20 & 4.74697162096552e-20 & 1 \tabularnewline
61 & 1.60824509322563e-20 & 3.21649018645125e-20 & 1 \tabularnewline
62 & 3.78243175135656e-21 & 7.56486350271313e-21 & 1 \tabularnewline
63 & 2.12533631081681e-19 & 4.25067262163362e-19 & 1 \tabularnewline
64 & 3.80346951377141e-19 & 7.60693902754282e-19 & 1 \tabularnewline
65 & 8.56304048513556e-18 & 1.71260809702711e-17 & 1 \tabularnewline
66 & 4.23808072281062e-17 & 8.47616144562125e-17 & 1 \tabularnewline
67 & 2.00442969784723e-15 & 4.00885939569446e-15 & 0.999999999999998 \tabularnewline
68 & 1.78616379756754e-14 & 3.57232759513508e-14 & 0.999999999999982 \tabularnewline
69 & 1.8965841185248e-14 & 3.7931682370496e-14 & 0.99999999999998 \tabularnewline
70 & 1.78188084897448e-13 & 3.56376169794897e-13 & 0.999999999999822 \tabularnewline
71 & 2.94484472716513e-13 & 5.88968945433026e-13 & 0.999999999999706 \tabularnewline
72 & 1.26748504590027e-13 & 2.53497009180054e-13 & 0.999999999999873 \tabularnewline
73 & 5.3230453131443e-14 & 1.06460906262886e-13 & 0.999999999999947 \tabularnewline
74 & 2.85210546919010e-14 & 5.70421093838021e-14 & 0.999999999999971 \tabularnewline
75 & 4.27336770328254e-14 & 8.54673540656509e-14 & 0.999999999999957 \tabularnewline
76 & 2.43189248751815e-14 & 4.8637849750363e-14 & 0.999999999999976 \tabularnewline
77 & 4.36949362829882e-14 & 8.73898725659765e-14 & 0.999999999999956 \tabularnewline
78 & 3.70946047655363e-14 & 7.41892095310726e-14 & 0.999999999999963 \tabularnewline
79 & 1.33393701045964e-13 & 2.66787402091928e-13 & 0.999999999999867 \tabularnewline
80 & 1.42229965515658e-12 & 2.84459931031316e-12 & 0.999999999998578 \tabularnewline
81 & 8.42132319830315e-13 & 1.68426463966063e-12 & 0.999999999999158 \tabularnewline
82 & 1.13361587130153e-12 & 2.26723174260306e-12 & 0.999999999998866 \tabularnewline
83 & 5.14545762706219e-13 & 1.02909152541244e-12 & 0.999999999999486 \tabularnewline
84 & 2.40445884284262e-13 & 4.80891768568524e-13 & 0.99999999999976 \tabularnewline
85 & 1.7262352601033e-13 & 3.4524705202066e-13 & 0.999999999999827 \tabularnewline
86 & 8.47076333903476e-14 & 1.69415266780695e-13 & 0.999999999999915 \tabularnewline
87 & 4.79401727094107e-14 & 9.58803454188215e-14 & 0.999999999999952 \tabularnewline
88 & 2.00763780660202e-14 & 4.01527561320404e-14 & 0.99999999999998 \tabularnewline
89 & 2.02296133366938e-14 & 4.04592266733876e-14 & 0.99999999999998 \tabularnewline
90 & 1.15141820603907e-14 & 2.30283641207814e-14 & 0.999999999999988 \tabularnewline
91 & 2.19225749858056e-14 & 4.38451499716112e-14 & 0.999999999999978 \tabularnewline
92 & 5.32896083186703e-14 & 1.06579216637341e-13 & 0.999999999999947 \tabularnewline
93 & 4.72273317372378e-14 & 9.44546634744756e-14 & 0.999999999999953 \tabularnewline
94 & 1.30452181753200e-13 & 2.60904363506399e-13 & 0.99999999999987 \tabularnewline
95 & 6.65209468115588e-14 & 1.33041893623118e-13 & 0.999999999999933 \tabularnewline
96 & 2.95898334328051e-13 & 5.91796668656101e-13 & 0.999999999999704 \tabularnewline
97 & 6.71889600726389e-13 & 1.34377920145278e-12 & 0.999999999999328 \tabularnewline
98 & 3.33121389980283e-13 & 6.66242779960566e-13 & 0.999999999999667 \tabularnewline
99 & 1.97780674055326e-13 & 3.95561348110652e-13 & 0.999999999999802 \tabularnewline
100 & 1.65921781036832e-13 & 3.31843562073664e-13 & 0.999999999999834 \tabularnewline
101 & 2.11624563176383e-13 & 4.23249126352766e-13 & 0.999999999999788 \tabularnewline
102 & 1.35958359583488e-13 & 2.71916719166976e-13 & 0.999999999999864 \tabularnewline
103 & 5.20307622889115e-13 & 1.04061524577823e-12 & 0.99999999999948 \tabularnewline
104 & 6.20805589376538e-13 & 1.24161117875308e-12 & 0.99999999999938 \tabularnewline
105 & 4.9437858827853e-13 & 9.8875717655706e-13 & 0.999999999999506 \tabularnewline
106 & 4.83815006522327e-13 & 9.67630013044653e-13 & 0.999999999999516 \tabularnewline
107 & 2.64650278502124e-13 & 5.29300557004248e-13 & 0.999999999999735 \tabularnewline
108 & 3.89249591453678e-13 & 7.78499182907356e-13 & 0.99999999999961 \tabularnewline
109 & 6.5963759864836e-13 & 1.31927519729672e-12 & 0.99999999999934 \tabularnewline
110 & 1.80551768011680e-12 & 3.61103536023359e-12 & 0.999999999998195 \tabularnewline
111 & 9.54811362085322e-13 & 1.90962272417064e-12 & 0.999999999999045 \tabularnewline
112 & 4.74674401639808e-13 & 9.49348803279616e-13 & 0.999999999999525 \tabularnewline
113 & 2.23185390792622e-13 & 4.46370781585244e-13 & 0.999999999999777 \tabularnewline
114 & 1.20540600418994e-13 & 2.41081200837987e-13 & 0.99999999999988 \tabularnewline
115 & 9.59336877342326e-14 & 1.91867375468465e-13 & 0.999999999999904 \tabularnewline
116 & 4.61884065104327e-14 & 9.23768130208653e-14 & 0.999999999999954 \tabularnewline
117 & 2.96682594854668e-14 & 5.93365189709337e-14 & 0.99999999999997 \tabularnewline
118 & 1.04223138666480e-13 & 2.08446277332961e-13 & 0.999999999999896 \tabularnewline
119 & 9.50967903739246e-14 & 1.90193580747849e-13 & 0.999999999999905 \tabularnewline
120 & 9.5475346635977e-14 & 1.90950693271954e-13 & 0.999999999999905 \tabularnewline
121 & 5.40388328782468e-14 & 1.08077665756494e-13 & 0.999999999999946 \tabularnewline
122 & 4.05033679718842e-14 & 8.10067359437683e-14 & 0.99999999999996 \tabularnewline
123 & 5.5707321599029e-14 & 1.11414643198058e-13 & 0.999999999999944 \tabularnewline
124 & 3.63849524505239e-14 & 7.27699049010479e-14 & 0.999999999999964 \tabularnewline
125 & 3.3053336048041e-14 & 6.6106672096082e-14 & 0.999999999999967 \tabularnewline
126 & 1.63736700924160e-14 & 3.27473401848319e-14 & 0.999999999999984 \tabularnewline
127 & 1.33610666292346e-14 & 2.67221332584693e-14 & 0.999999999999987 \tabularnewline
128 & 6.60935313286634e-15 & 1.32187062657327e-14 & 0.999999999999993 \tabularnewline
129 & 4.25992559212226e-15 & 8.51985118424451e-15 & 0.999999999999996 \tabularnewline
130 & 3.77975009256245e-15 & 7.5595001851249e-15 & 0.999999999999996 \tabularnewline
131 & 8.37442279490573e-14 & 1.67488455898115e-13 & 0.999999999999916 \tabularnewline
132 & 1.90219792785771e-13 & 3.80439585571543e-13 & 0.99999999999981 \tabularnewline
133 & 8.0227588862421e-13 & 1.60455177724842e-12 & 0.999999999999198 \tabularnewline
134 & 1.69993624886529e-12 & 3.39987249773058e-12 & 0.9999999999983 \tabularnewline
135 & 6.58622302312026e-12 & 1.31724460462405e-11 & 0.999999999993414 \tabularnewline
136 & 1.32072683433539e-10 & 2.64145366867078e-10 & 0.999999999867927 \tabularnewline
137 & 1.22641995495029e-09 & 2.45283990990058e-09 & 0.99999999877358 \tabularnewline
138 & 1.95107568685006e-09 & 3.90215137370012e-09 & 0.999999998048924 \tabularnewline
139 & 7.25717949984008e-09 & 1.45143589996802e-08 & 0.99999999274282 \tabularnewline
140 & 1.55032084719504e-08 & 3.10064169439009e-08 & 0.999999984496792 \tabularnewline
141 & 2.25789902030801e-08 & 4.51579804061602e-08 & 0.99999997742101 \tabularnewline
142 & 3.25816426196389e-08 & 6.51632852392778e-08 & 0.999999967418357 \tabularnewline
143 & 2.90280923171368e-08 & 5.80561846342736e-08 & 0.999999970971908 \tabularnewline
144 & 2.94775996746386e-08 & 5.89551993492773e-08 & 0.9999999705224 \tabularnewline
145 & 4.03697221245785e-08 & 8.0739444249157e-08 & 0.999999959630278 \tabularnewline
146 & 2.26256948338941e-08 & 4.52513896677882e-08 & 0.999999977374305 \tabularnewline
147 & 1.48306481412101e-08 & 2.96612962824201e-08 & 0.999999985169352 \tabularnewline
148 & 1.08509180321529e-08 & 2.17018360643059e-08 & 0.999999989149082 \tabularnewline
149 & 1.74001224656958e-08 & 3.48002449313917e-08 & 0.999999982599878 \tabularnewline
150 & 2.42394274072340e-08 & 4.84788548144679e-08 & 0.999999975760573 \tabularnewline
151 & 1.11506659574462e-07 & 2.23013319148924e-07 & 0.99999988849334 \tabularnewline
152 & 2.61161362642186e-07 & 5.22322725284373e-07 & 0.999999738838637 \tabularnewline
153 & 3.78163186232042e-07 & 7.56326372464085e-07 & 0.999999621836814 \tabularnewline
154 & 6.16201653667139e-07 & 1.23240330733428e-06 & 0.999999383798346 \tabularnewline
155 & 7.03562966720508e-07 & 1.40712593344102e-06 & 0.999999296437033 \tabularnewline
156 & 1.00002580305371e-06 & 2.00005160610742e-06 & 0.999998999974197 \tabularnewline
157 & 8.08677236035394e-07 & 1.61735447207079e-06 & 0.999999191322764 \tabularnewline
158 & 8.00208492201118e-07 & 1.60041698440224e-06 & 0.999999199791508 \tabularnewline
159 & 1.17507253018197e-06 & 2.35014506036394e-06 & 0.99999882492747 \tabularnewline
160 & 9.42065418988267e-07 & 1.88413083797653e-06 & 0.999999057934581 \tabularnewline
161 & 1.47419520981919e-06 & 2.94839041963838e-06 & 0.99999852580479 \tabularnewline
162 & 2.53386343851803e-06 & 5.06772687703607e-06 & 0.999997466136561 \tabularnewline
163 & 1.07326358467037e-05 & 2.14652716934074e-05 & 0.999989267364153 \tabularnewline
164 & 2.66190733678372e-05 & 5.32381467356745e-05 & 0.999973380926632 \tabularnewline
165 & 3.16882924828982e-05 & 6.33765849657964e-05 & 0.999968311707517 \tabularnewline
166 & 5.50800759168271e-05 & 0.000110160151833654 & 0.999944919924083 \tabularnewline
167 & 7.72361789337881e-05 & 0.000154472357867576 & 0.999922763821066 \tabularnewline
168 & 0.000141723006220823 & 0.000283446012441646 & 0.99985827699378 \tabularnewline
169 & 0.000161256815125966 & 0.000322513630251933 & 0.999838743184874 \tabularnewline
170 & 0.000333878759050045 & 0.00066775751810009 & 0.99966612124095 \tabularnewline
171 & 0.00063454109592438 & 0.00126908219184876 & 0.999365458904076 \tabularnewline
172 & 0.000477430131656485 & 0.00095486026331297 & 0.999522569868344 \tabularnewline
173 & 0.000560707216486152 & 0.00112141443297230 & 0.999439292783514 \tabularnewline
174 & 0.00059219445871566 & 0.00118438891743132 & 0.999407805541284 \tabularnewline
175 & 0.00123928016857481 & 0.00247856033714962 & 0.998760719831425 \tabularnewline
176 & 0.00215940850319108 & 0.00431881700638215 & 0.99784059149681 \tabularnewline
177 & 0.00216517233908968 & 0.00433034467817935 & 0.99783482766091 \tabularnewline
178 & 0.00362434120434522 & 0.00724868240869045 & 0.996375658795655 \tabularnewline
179 & 0.00349985995777208 & 0.00699971991554417 & 0.996500140042228 \tabularnewline
180 & 0.00304966708109752 & 0.00609933416219503 & 0.996950332918902 \tabularnewline
181 & 0.0025449155847961 & 0.0050898311695922 & 0.997455084415204 \tabularnewline
182 & 0.00231897236412072 & 0.00463794472824144 & 0.99768102763588 \tabularnewline
183 & 0.00152121839554183 & 0.00304243679108367 & 0.998478781604458 \tabularnewline
184 & 0.00122167453969259 & 0.00244334907938518 & 0.998778325460307 \tabularnewline
185 & 0.000889202039780004 & 0.00177840407956001 & 0.99911079796022 \tabularnewline
186 & 0.000660303990990489 & 0.00132060798198098 & 0.99933969600901 \tabularnewline
187 & 0.000715512340939494 & 0.00143102468187899 & 0.99928448765906 \tabularnewline
188 & 0.000565520969713227 & 0.00113104193942645 & 0.999434479030287 \tabularnewline
189 & 0.000344067412124037 & 0.000688134824248074 & 0.999655932587876 \tabularnewline
190 & 0.000223120638541145 & 0.00044624127708229 & 0.99977687936146 \tabularnewline
191 & 0.000150459841760544 & 0.000300919683521088 & 0.99984954015824 \tabularnewline
192 & 9.63589849091027e-05 & 0.000192717969818205 & 0.99990364101509 \tabularnewline
193 & 8.78637575049426e-05 & 0.000175727515009885 & 0.999912136242495 \tabularnewline
194 & 9.67131993851262e-05 & 0.000193426398770252 & 0.999903286800615 \tabularnewline
195 & 0.000113387645918150 & 0.000226775291836301 & 0.999886612354082 \tabularnewline
196 & 0.000721415661865119 & 0.00144283132373024 & 0.999278584338135 \tabularnewline
197 & 0.0014702461562499 & 0.0029404923124998 & 0.99852975384375 \tabularnewline
198 & 0.00474684860031214 & 0.00949369720062428 & 0.995253151399688 \tabularnewline
199 & 0.00480608946407544 & 0.00961217892815087 & 0.995193910535925 \tabularnewline
200 & 0.00392914471340299 & 0.00785828942680599 & 0.996070855286597 \tabularnewline
201 & 0.00438290831766447 & 0.00876581663532894 & 0.995617091682335 \tabularnewline
202 & 0.00467170143642404 & 0.00934340287284808 & 0.995328298563576 \tabularnewline
203 & 0.00584224113637679 & 0.0116844822727536 & 0.994157758863623 \tabularnewline
204 & 0.00586034954756417 & 0.0117206990951283 & 0.994139650452436 \tabularnewline
205 & 0.00660610397076742 & 0.0132122079415348 & 0.993393896029233 \tabularnewline
206 & 0.00700828657886787 & 0.0140165731577357 & 0.992991713421132 \tabularnewline
207 & 0.00682712311572777 & 0.0136542462314555 & 0.993172876884272 \tabularnewline
208 & 0.953043106227799 & 0.0939137875444028 & 0.0469568937722014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&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]18[/C][C]0.0122354432408082[/C][C]0.0244708864816165[/C][C]0.987764556759192[/C][/ROW]
[ROW][C]19[/C][C]0.0146018275626955[/C][C]0.0292036551253910[/C][C]0.985398172437304[/C][/ROW]
[ROW][C]20[/C][C]0.00702121328060735[/C][C]0.0140424265612147[/C][C]0.992978786719393[/C][/ROW]
[ROW][C]21[/C][C]0.0025732221047679[/C][C]0.0051464442095358[/C][C]0.997426777895232[/C][/ROW]
[ROW][C]22[/C][C]0.00167560693402365[/C][C]0.00335121386804731[/C][C]0.998324393065976[/C][/ROW]
[ROW][C]23[/C][C]0.000478949747036666[/C][C]0.000957899494073333[/C][C]0.999521050252963[/C][/ROW]
[ROW][C]24[/C][C]0.000133075263899154[/C][C]0.000266150527798308[/C][C]0.9998669247361[/C][/ROW]
[ROW][C]25[/C][C]3.78976755697904e-05[/C][C]7.57953511395807e-05[/C][C]0.99996210232443[/C][/ROW]
[ROW][C]26[/C][C]1.30367673116642e-05[/C][C]2.60735346233283e-05[/C][C]0.999986963232688[/C][/ROW]
[ROW][C]27[/C][C]1.00845442344891e-05[/C][C]2.01690884689783e-05[/C][C]0.999989915455765[/C][/ROW]
[ROW][C]28[/C][C]3.29626021688009e-06[/C][C]6.59252043376018e-06[/C][C]0.999996703739783[/C][/ROW]
[ROW][C]29[/C][C]1.04569341416315e-06[/C][C]2.09138682832631e-06[/C][C]0.999998954306586[/C][/ROW]
[ROW][C]30[/C][C]2.64087323432895e-07[/C][C]5.28174646865791e-07[/C][C]0.999999735912677[/C][/ROW]
[ROW][C]31[/C][C]1.01618992792257e-07[/C][C]2.03237985584515e-07[/C][C]0.999999898381007[/C][/ROW]
[ROW][C]32[/C][C]2.76997288697144e-08[/C][C]5.53994577394287e-08[/C][C]0.99999997230027[/C][/ROW]
[ROW][C]33[/C][C]9.70075522821916e-09[/C][C]1.94015104564383e-08[/C][C]0.999999990299245[/C][/ROW]
[ROW][C]34[/C][C]2.37595593097028e-09[/C][C]4.75191186194057e-09[/C][C]0.999999997624044[/C][/ROW]
[ROW][C]35[/C][C]5.58575303035896e-10[/C][C]1.11715060607179e-09[/C][C]0.999999999441425[/C][/ROW]
[ROW][C]36[/C][C]1.53669526402525e-10[/C][C]3.07339052805049e-10[/C][C]0.99999999984633[/C][/ROW]
[ROW][C]37[/C][C]4.40128233857026e-11[/C][C]8.80256467714051e-11[/C][C]0.999999999955987[/C][/ROW]
[ROW][C]38[/C][C]3.22811810582960e-11[/C][C]6.45623621165921e-11[/C][C]0.999999999967719[/C][/ROW]
[ROW][C]39[/C][C]1.17060788176721e-11[/C][C]2.34121576353442e-11[/C][C]0.999999999988294[/C][/ROW]
[ROW][C]40[/C][C]2.69404074882562e-12[/C][C]5.38808149765123e-12[/C][C]0.999999999997306[/C][/ROW]
[ROW][C]41[/C][C]7.14080940462448e-13[/C][C]1.42816188092490e-12[/C][C]0.999999999999286[/C][/ROW]
[ROW][C]42[/C][C]2.42305714623048e-13[/C][C]4.84611429246095e-13[/C][C]0.999999999999758[/C][/ROW]
[ROW][C]43[/C][C]7.9722274520021e-14[/C][C]1.59444549040042e-13[/C][C]0.99999999999992[/C][/ROW]
[ROW][C]44[/C][C]3.35724194015635e-14[/C][C]6.7144838803127e-14[/C][C]0.999999999999966[/C][/ROW]
[ROW][C]45[/C][C]7.46287852060801e-15[/C][C]1.49257570412160e-14[/C][C]0.999999999999993[/C][/ROW]
[ROW][C]46[/C][C]2.07155693867398e-15[/C][C]4.14311387734796e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]47[/C][C]4.776713732852e-16[/C][C]9.553427465704e-16[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]1.12240157060166e-16[/C][C]2.24480314120331e-16[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]1.07140039870849e-16[/C][C]2.14280079741698e-16[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]3.17136418486792e-17[/C][C]6.34272836973584e-17[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]4.70535483396168e-17[/C][C]9.41070966792336e-17[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]1.42936159091933e-17[/C][C]2.85872318183867e-17[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]4.57013867308219e-18[/C][C]9.14027734616439e-18[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]1.95605589310648e-18[/C][C]3.91211178621295e-18[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]8.92617700819325e-19[/C][C]1.78523540163865e-18[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]3.05258966150060e-19[/C][C]6.10517932300119e-19[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]1.39944514369905e-19[/C][C]2.79889028739810e-19[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]1.72464097794075e-19[/C][C]3.44928195588149e-19[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]8.40808303232644e-20[/C][C]1.68161660646529e-19[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]2.37348581048276e-20[/C][C]4.74697162096552e-20[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]1.60824509322563e-20[/C][C]3.21649018645125e-20[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]3.78243175135656e-21[/C][C]7.56486350271313e-21[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]2.12533631081681e-19[/C][C]4.25067262163362e-19[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]3.80346951377141e-19[/C][C]7.60693902754282e-19[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]8.56304048513556e-18[/C][C]1.71260809702711e-17[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]4.23808072281062e-17[/C][C]8.47616144562125e-17[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]2.00442969784723e-15[/C][C]4.00885939569446e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]68[/C][C]1.78616379756754e-14[/C][C]3.57232759513508e-14[/C][C]0.999999999999982[/C][/ROW]
[ROW][C]69[/C][C]1.8965841185248e-14[/C][C]3.7931682370496e-14[/C][C]0.99999999999998[/C][/ROW]
[ROW][C]70[/C][C]1.78188084897448e-13[/C][C]3.56376169794897e-13[/C][C]0.999999999999822[/C][/ROW]
[ROW][C]71[/C][C]2.94484472716513e-13[/C][C]5.88968945433026e-13[/C][C]0.999999999999706[/C][/ROW]
[ROW][C]72[/C][C]1.26748504590027e-13[/C][C]2.53497009180054e-13[/C][C]0.999999999999873[/C][/ROW]
[ROW][C]73[/C][C]5.3230453131443e-14[/C][C]1.06460906262886e-13[/C][C]0.999999999999947[/C][/ROW]
[ROW][C]74[/C][C]2.85210546919010e-14[/C][C]5.70421093838021e-14[/C][C]0.999999999999971[/C][/ROW]
[ROW][C]75[/C][C]4.27336770328254e-14[/C][C]8.54673540656509e-14[/C][C]0.999999999999957[/C][/ROW]
[ROW][C]76[/C][C]2.43189248751815e-14[/C][C]4.8637849750363e-14[/C][C]0.999999999999976[/C][/ROW]
[ROW][C]77[/C][C]4.36949362829882e-14[/C][C]8.73898725659765e-14[/C][C]0.999999999999956[/C][/ROW]
[ROW][C]78[/C][C]3.70946047655363e-14[/C][C]7.41892095310726e-14[/C][C]0.999999999999963[/C][/ROW]
[ROW][C]79[/C][C]1.33393701045964e-13[/C][C]2.66787402091928e-13[/C][C]0.999999999999867[/C][/ROW]
[ROW][C]80[/C][C]1.42229965515658e-12[/C][C]2.84459931031316e-12[/C][C]0.999999999998578[/C][/ROW]
[ROW][C]81[/C][C]8.42132319830315e-13[/C][C]1.68426463966063e-12[/C][C]0.999999999999158[/C][/ROW]
[ROW][C]82[/C][C]1.13361587130153e-12[/C][C]2.26723174260306e-12[/C][C]0.999999999998866[/C][/ROW]
[ROW][C]83[/C][C]5.14545762706219e-13[/C][C]1.02909152541244e-12[/C][C]0.999999999999486[/C][/ROW]
[ROW][C]84[/C][C]2.40445884284262e-13[/C][C]4.80891768568524e-13[/C][C]0.99999999999976[/C][/ROW]
[ROW][C]85[/C][C]1.7262352601033e-13[/C][C]3.4524705202066e-13[/C][C]0.999999999999827[/C][/ROW]
[ROW][C]86[/C][C]8.47076333903476e-14[/C][C]1.69415266780695e-13[/C][C]0.999999999999915[/C][/ROW]
[ROW][C]87[/C][C]4.79401727094107e-14[/C][C]9.58803454188215e-14[/C][C]0.999999999999952[/C][/ROW]
[ROW][C]88[/C][C]2.00763780660202e-14[/C][C]4.01527561320404e-14[/C][C]0.99999999999998[/C][/ROW]
[ROW][C]89[/C][C]2.02296133366938e-14[/C][C]4.04592266733876e-14[/C][C]0.99999999999998[/C][/ROW]
[ROW][C]90[/C][C]1.15141820603907e-14[/C][C]2.30283641207814e-14[/C][C]0.999999999999988[/C][/ROW]
[ROW][C]91[/C][C]2.19225749858056e-14[/C][C]4.38451499716112e-14[/C][C]0.999999999999978[/C][/ROW]
[ROW][C]92[/C][C]5.32896083186703e-14[/C][C]1.06579216637341e-13[/C][C]0.999999999999947[/C][/ROW]
[ROW][C]93[/C][C]4.72273317372378e-14[/C][C]9.44546634744756e-14[/C][C]0.999999999999953[/C][/ROW]
[ROW][C]94[/C][C]1.30452181753200e-13[/C][C]2.60904363506399e-13[/C][C]0.99999999999987[/C][/ROW]
[ROW][C]95[/C][C]6.65209468115588e-14[/C][C]1.33041893623118e-13[/C][C]0.999999999999933[/C][/ROW]
[ROW][C]96[/C][C]2.95898334328051e-13[/C][C]5.91796668656101e-13[/C][C]0.999999999999704[/C][/ROW]
[ROW][C]97[/C][C]6.71889600726389e-13[/C][C]1.34377920145278e-12[/C][C]0.999999999999328[/C][/ROW]
[ROW][C]98[/C][C]3.33121389980283e-13[/C][C]6.66242779960566e-13[/C][C]0.999999999999667[/C][/ROW]
[ROW][C]99[/C][C]1.97780674055326e-13[/C][C]3.95561348110652e-13[/C][C]0.999999999999802[/C][/ROW]
[ROW][C]100[/C][C]1.65921781036832e-13[/C][C]3.31843562073664e-13[/C][C]0.999999999999834[/C][/ROW]
[ROW][C]101[/C][C]2.11624563176383e-13[/C][C]4.23249126352766e-13[/C][C]0.999999999999788[/C][/ROW]
[ROW][C]102[/C][C]1.35958359583488e-13[/C][C]2.71916719166976e-13[/C][C]0.999999999999864[/C][/ROW]
[ROW][C]103[/C][C]5.20307622889115e-13[/C][C]1.04061524577823e-12[/C][C]0.99999999999948[/C][/ROW]
[ROW][C]104[/C][C]6.20805589376538e-13[/C][C]1.24161117875308e-12[/C][C]0.99999999999938[/C][/ROW]
[ROW][C]105[/C][C]4.9437858827853e-13[/C][C]9.8875717655706e-13[/C][C]0.999999999999506[/C][/ROW]
[ROW][C]106[/C][C]4.83815006522327e-13[/C][C]9.67630013044653e-13[/C][C]0.999999999999516[/C][/ROW]
[ROW][C]107[/C][C]2.64650278502124e-13[/C][C]5.29300557004248e-13[/C][C]0.999999999999735[/C][/ROW]
[ROW][C]108[/C][C]3.89249591453678e-13[/C][C]7.78499182907356e-13[/C][C]0.99999999999961[/C][/ROW]
[ROW][C]109[/C][C]6.5963759864836e-13[/C][C]1.31927519729672e-12[/C][C]0.99999999999934[/C][/ROW]
[ROW][C]110[/C][C]1.80551768011680e-12[/C][C]3.61103536023359e-12[/C][C]0.999999999998195[/C][/ROW]
[ROW][C]111[/C][C]9.54811362085322e-13[/C][C]1.90962272417064e-12[/C][C]0.999999999999045[/C][/ROW]
[ROW][C]112[/C][C]4.74674401639808e-13[/C][C]9.49348803279616e-13[/C][C]0.999999999999525[/C][/ROW]
[ROW][C]113[/C][C]2.23185390792622e-13[/C][C]4.46370781585244e-13[/C][C]0.999999999999777[/C][/ROW]
[ROW][C]114[/C][C]1.20540600418994e-13[/C][C]2.41081200837987e-13[/C][C]0.99999999999988[/C][/ROW]
[ROW][C]115[/C][C]9.59336877342326e-14[/C][C]1.91867375468465e-13[/C][C]0.999999999999904[/C][/ROW]
[ROW][C]116[/C][C]4.61884065104327e-14[/C][C]9.23768130208653e-14[/C][C]0.999999999999954[/C][/ROW]
[ROW][C]117[/C][C]2.96682594854668e-14[/C][C]5.93365189709337e-14[/C][C]0.99999999999997[/C][/ROW]
[ROW][C]118[/C][C]1.04223138666480e-13[/C][C]2.08446277332961e-13[/C][C]0.999999999999896[/C][/ROW]
[ROW][C]119[/C][C]9.50967903739246e-14[/C][C]1.90193580747849e-13[/C][C]0.999999999999905[/C][/ROW]
[ROW][C]120[/C][C]9.5475346635977e-14[/C][C]1.90950693271954e-13[/C][C]0.999999999999905[/C][/ROW]
[ROW][C]121[/C][C]5.40388328782468e-14[/C][C]1.08077665756494e-13[/C][C]0.999999999999946[/C][/ROW]
[ROW][C]122[/C][C]4.05033679718842e-14[/C][C]8.10067359437683e-14[/C][C]0.99999999999996[/C][/ROW]
[ROW][C]123[/C][C]5.5707321599029e-14[/C][C]1.11414643198058e-13[/C][C]0.999999999999944[/C][/ROW]
[ROW][C]124[/C][C]3.63849524505239e-14[/C][C]7.27699049010479e-14[/C][C]0.999999999999964[/C][/ROW]
[ROW][C]125[/C][C]3.3053336048041e-14[/C][C]6.6106672096082e-14[/C][C]0.999999999999967[/C][/ROW]
[ROW][C]126[/C][C]1.63736700924160e-14[/C][C]3.27473401848319e-14[/C][C]0.999999999999984[/C][/ROW]
[ROW][C]127[/C][C]1.33610666292346e-14[/C][C]2.67221332584693e-14[/C][C]0.999999999999987[/C][/ROW]
[ROW][C]128[/C][C]6.60935313286634e-15[/C][C]1.32187062657327e-14[/C][C]0.999999999999993[/C][/ROW]
[ROW][C]129[/C][C]4.25992559212226e-15[/C][C]8.51985118424451e-15[/C][C]0.999999999999996[/C][/ROW]
[ROW][C]130[/C][C]3.77975009256245e-15[/C][C]7.5595001851249e-15[/C][C]0.999999999999996[/C][/ROW]
[ROW][C]131[/C][C]8.37442279490573e-14[/C][C]1.67488455898115e-13[/C][C]0.999999999999916[/C][/ROW]
[ROW][C]132[/C][C]1.90219792785771e-13[/C][C]3.80439585571543e-13[/C][C]0.99999999999981[/C][/ROW]
[ROW][C]133[/C][C]8.0227588862421e-13[/C][C]1.60455177724842e-12[/C][C]0.999999999999198[/C][/ROW]
[ROW][C]134[/C][C]1.69993624886529e-12[/C][C]3.39987249773058e-12[/C][C]0.9999999999983[/C][/ROW]
[ROW][C]135[/C][C]6.58622302312026e-12[/C][C]1.31724460462405e-11[/C][C]0.999999999993414[/C][/ROW]
[ROW][C]136[/C][C]1.32072683433539e-10[/C][C]2.64145366867078e-10[/C][C]0.999999999867927[/C][/ROW]
[ROW][C]137[/C][C]1.22641995495029e-09[/C][C]2.45283990990058e-09[/C][C]0.99999999877358[/C][/ROW]
[ROW][C]138[/C][C]1.95107568685006e-09[/C][C]3.90215137370012e-09[/C][C]0.999999998048924[/C][/ROW]
[ROW][C]139[/C][C]7.25717949984008e-09[/C][C]1.45143589996802e-08[/C][C]0.99999999274282[/C][/ROW]
[ROW][C]140[/C][C]1.55032084719504e-08[/C][C]3.10064169439009e-08[/C][C]0.999999984496792[/C][/ROW]
[ROW][C]141[/C][C]2.25789902030801e-08[/C][C]4.51579804061602e-08[/C][C]0.99999997742101[/C][/ROW]
[ROW][C]142[/C][C]3.25816426196389e-08[/C][C]6.51632852392778e-08[/C][C]0.999999967418357[/C][/ROW]
[ROW][C]143[/C][C]2.90280923171368e-08[/C][C]5.80561846342736e-08[/C][C]0.999999970971908[/C][/ROW]
[ROW][C]144[/C][C]2.94775996746386e-08[/C][C]5.89551993492773e-08[/C][C]0.9999999705224[/C][/ROW]
[ROW][C]145[/C][C]4.03697221245785e-08[/C][C]8.0739444249157e-08[/C][C]0.999999959630278[/C][/ROW]
[ROW][C]146[/C][C]2.26256948338941e-08[/C][C]4.52513896677882e-08[/C][C]0.999999977374305[/C][/ROW]
[ROW][C]147[/C][C]1.48306481412101e-08[/C][C]2.96612962824201e-08[/C][C]0.999999985169352[/C][/ROW]
[ROW][C]148[/C][C]1.08509180321529e-08[/C][C]2.17018360643059e-08[/C][C]0.999999989149082[/C][/ROW]
[ROW][C]149[/C][C]1.74001224656958e-08[/C][C]3.48002449313917e-08[/C][C]0.999999982599878[/C][/ROW]
[ROW][C]150[/C][C]2.42394274072340e-08[/C][C]4.84788548144679e-08[/C][C]0.999999975760573[/C][/ROW]
[ROW][C]151[/C][C]1.11506659574462e-07[/C][C]2.23013319148924e-07[/C][C]0.99999988849334[/C][/ROW]
[ROW][C]152[/C][C]2.61161362642186e-07[/C][C]5.22322725284373e-07[/C][C]0.999999738838637[/C][/ROW]
[ROW][C]153[/C][C]3.78163186232042e-07[/C][C]7.56326372464085e-07[/C][C]0.999999621836814[/C][/ROW]
[ROW][C]154[/C][C]6.16201653667139e-07[/C][C]1.23240330733428e-06[/C][C]0.999999383798346[/C][/ROW]
[ROW][C]155[/C][C]7.03562966720508e-07[/C][C]1.40712593344102e-06[/C][C]0.999999296437033[/C][/ROW]
[ROW][C]156[/C][C]1.00002580305371e-06[/C][C]2.00005160610742e-06[/C][C]0.999998999974197[/C][/ROW]
[ROW][C]157[/C][C]8.08677236035394e-07[/C][C]1.61735447207079e-06[/C][C]0.999999191322764[/C][/ROW]
[ROW][C]158[/C][C]8.00208492201118e-07[/C][C]1.60041698440224e-06[/C][C]0.999999199791508[/C][/ROW]
[ROW][C]159[/C][C]1.17507253018197e-06[/C][C]2.35014506036394e-06[/C][C]0.99999882492747[/C][/ROW]
[ROW][C]160[/C][C]9.42065418988267e-07[/C][C]1.88413083797653e-06[/C][C]0.999999057934581[/C][/ROW]
[ROW][C]161[/C][C]1.47419520981919e-06[/C][C]2.94839041963838e-06[/C][C]0.99999852580479[/C][/ROW]
[ROW][C]162[/C][C]2.53386343851803e-06[/C][C]5.06772687703607e-06[/C][C]0.999997466136561[/C][/ROW]
[ROW][C]163[/C][C]1.07326358467037e-05[/C][C]2.14652716934074e-05[/C][C]0.999989267364153[/C][/ROW]
[ROW][C]164[/C][C]2.66190733678372e-05[/C][C]5.32381467356745e-05[/C][C]0.999973380926632[/C][/ROW]
[ROW][C]165[/C][C]3.16882924828982e-05[/C][C]6.33765849657964e-05[/C][C]0.999968311707517[/C][/ROW]
[ROW][C]166[/C][C]5.50800759168271e-05[/C][C]0.000110160151833654[/C][C]0.999944919924083[/C][/ROW]
[ROW][C]167[/C][C]7.72361789337881e-05[/C][C]0.000154472357867576[/C][C]0.999922763821066[/C][/ROW]
[ROW][C]168[/C][C]0.000141723006220823[/C][C]0.000283446012441646[/C][C]0.99985827699378[/C][/ROW]
[ROW][C]169[/C][C]0.000161256815125966[/C][C]0.000322513630251933[/C][C]0.999838743184874[/C][/ROW]
[ROW][C]170[/C][C]0.000333878759050045[/C][C]0.00066775751810009[/C][C]0.99966612124095[/C][/ROW]
[ROW][C]171[/C][C]0.00063454109592438[/C][C]0.00126908219184876[/C][C]0.999365458904076[/C][/ROW]
[ROW][C]172[/C][C]0.000477430131656485[/C][C]0.00095486026331297[/C][C]0.999522569868344[/C][/ROW]
[ROW][C]173[/C][C]0.000560707216486152[/C][C]0.00112141443297230[/C][C]0.999439292783514[/C][/ROW]
[ROW][C]174[/C][C]0.00059219445871566[/C][C]0.00118438891743132[/C][C]0.999407805541284[/C][/ROW]
[ROW][C]175[/C][C]0.00123928016857481[/C][C]0.00247856033714962[/C][C]0.998760719831425[/C][/ROW]
[ROW][C]176[/C][C]0.00215940850319108[/C][C]0.00431881700638215[/C][C]0.99784059149681[/C][/ROW]
[ROW][C]177[/C][C]0.00216517233908968[/C][C]0.00433034467817935[/C][C]0.99783482766091[/C][/ROW]
[ROW][C]178[/C][C]0.00362434120434522[/C][C]0.00724868240869045[/C][C]0.996375658795655[/C][/ROW]
[ROW][C]179[/C][C]0.00349985995777208[/C][C]0.00699971991554417[/C][C]0.996500140042228[/C][/ROW]
[ROW][C]180[/C][C]0.00304966708109752[/C][C]0.00609933416219503[/C][C]0.996950332918902[/C][/ROW]
[ROW][C]181[/C][C]0.0025449155847961[/C][C]0.0050898311695922[/C][C]0.997455084415204[/C][/ROW]
[ROW][C]182[/C][C]0.00231897236412072[/C][C]0.00463794472824144[/C][C]0.99768102763588[/C][/ROW]
[ROW][C]183[/C][C]0.00152121839554183[/C][C]0.00304243679108367[/C][C]0.998478781604458[/C][/ROW]
[ROW][C]184[/C][C]0.00122167453969259[/C][C]0.00244334907938518[/C][C]0.998778325460307[/C][/ROW]
[ROW][C]185[/C][C]0.000889202039780004[/C][C]0.00177840407956001[/C][C]0.99911079796022[/C][/ROW]
[ROW][C]186[/C][C]0.000660303990990489[/C][C]0.00132060798198098[/C][C]0.99933969600901[/C][/ROW]
[ROW][C]187[/C][C]0.000715512340939494[/C][C]0.00143102468187899[/C][C]0.99928448765906[/C][/ROW]
[ROW][C]188[/C][C]0.000565520969713227[/C][C]0.00113104193942645[/C][C]0.999434479030287[/C][/ROW]
[ROW][C]189[/C][C]0.000344067412124037[/C][C]0.000688134824248074[/C][C]0.999655932587876[/C][/ROW]
[ROW][C]190[/C][C]0.000223120638541145[/C][C]0.00044624127708229[/C][C]0.99977687936146[/C][/ROW]
[ROW][C]191[/C][C]0.000150459841760544[/C][C]0.000300919683521088[/C][C]0.99984954015824[/C][/ROW]
[ROW][C]192[/C][C]9.63589849091027e-05[/C][C]0.000192717969818205[/C][C]0.99990364101509[/C][/ROW]
[ROW][C]193[/C][C]8.78637575049426e-05[/C][C]0.000175727515009885[/C][C]0.999912136242495[/C][/ROW]
[ROW][C]194[/C][C]9.67131993851262e-05[/C][C]0.000193426398770252[/C][C]0.999903286800615[/C][/ROW]
[ROW][C]195[/C][C]0.000113387645918150[/C][C]0.000226775291836301[/C][C]0.999886612354082[/C][/ROW]
[ROW][C]196[/C][C]0.000721415661865119[/C][C]0.00144283132373024[/C][C]0.999278584338135[/C][/ROW]
[ROW][C]197[/C][C]0.0014702461562499[/C][C]0.0029404923124998[/C][C]0.99852975384375[/C][/ROW]
[ROW][C]198[/C][C]0.00474684860031214[/C][C]0.00949369720062428[/C][C]0.995253151399688[/C][/ROW]
[ROW][C]199[/C][C]0.00480608946407544[/C][C]0.00961217892815087[/C][C]0.995193910535925[/C][/ROW]
[ROW][C]200[/C][C]0.00392914471340299[/C][C]0.00785828942680599[/C][C]0.996070855286597[/C][/ROW]
[ROW][C]201[/C][C]0.00438290831766447[/C][C]0.00876581663532894[/C][C]0.995617091682335[/C][/ROW]
[ROW][C]202[/C][C]0.00467170143642404[/C][C]0.00934340287284808[/C][C]0.995328298563576[/C][/ROW]
[ROW][C]203[/C][C]0.00584224113637679[/C][C]0.0116844822727536[/C][C]0.994157758863623[/C][/ROW]
[ROW][C]204[/C][C]0.00586034954756417[/C][C]0.0117206990951283[/C][C]0.994139650452436[/C][/ROW]
[ROW][C]205[/C][C]0.00660610397076742[/C][C]0.0132122079415348[/C][C]0.993393896029233[/C][/ROW]
[ROW][C]206[/C][C]0.00700828657886787[/C][C]0.0140165731577357[/C][C]0.992991713421132[/C][/ROW]
[ROW][C]207[/C][C]0.00682712311572777[/C][C]0.0136542462314555[/C][C]0.993172876884272[/C][/ROW]
[ROW][C]208[/C][C]0.953043106227799[/C][C]0.0939137875444028[/C][C]0.0469568937722014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
180.01223544324080820.02447088648161650.987764556759192
190.01460182756269550.02920365512539100.985398172437304
200.007021213280607350.01404242656121470.992978786719393
210.00257322210476790.00514644420953580.997426777895232
220.001675606934023650.003351213868047310.998324393065976
230.0004789497470366660.0009578994940733330.999521050252963
240.0001330752638991540.0002661505277983080.9998669247361
253.78976755697904e-057.57953511395807e-050.99996210232443
261.30367673116642e-052.60735346233283e-050.999986963232688
271.00845442344891e-052.01690884689783e-050.999989915455765
283.29626021688009e-066.59252043376018e-060.999996703739783
291.04569341416315e-062.09138682832631e-060.999998954306586
302.64087323432895e-075.28174646865791e-070.999999735912677
311.01618992792257e-072.03237985584515e-070.999999898381007
322.76997288697144e-085.53994577394287e-080.99999997230027
339.70075522821916e-091.94015104564383e-080.999999990299245
342.37595593097028e-094.75191186194057e-090.999999997624044
355.58575303035896e-101.11715060607179e-090.999999999441425
361.53669526402525e-103.07339052805049e-100.99999999984633
374.40128233857026e-118.80256467714051e-110.999999999955987
383.22811810582960e-116.45623621165921e-110.999999999967719
391.17060788176721e-112.34121576353442e-110.999999999988294
402.69404074882562e-125.38808149765123e-120.999999999997306
417.14080940462448e-131.42816188092490e-120.999999999999286
422.42305714623048e-134.84611429246095e-130.999999999999758
437.9722274520021e-141.59444549040042e-130.99999999999992
443.35724194015635e-146.7144838803127e-140.999999999999966
457.46287852060801e-151.49257570412160e-140.999999999999993
462.07155693867398e-154.14311387734796e-150.999999999999998
474.776713732852e-169.553427465704e-161
481.12240157060166e-162.24480314120331e-161
491.07140039870849e-162.14280079741698e-161
503.17136418486792e-176.34272836973584e-171
514.70535483396168e-179.41070966792336e-171
521.42936159091933e-172.85872318183867e-171
534.57013867308219e-189.14027734616439e-181
541.95605589310648e-183.91211178621295e-181
558.92617700819325e-191.78523540163865e-181
563.05258966150060e-196.10517932300119e-191
571.39944514369905e-192.79889028739810e-191
581.72464097794075e-193.44928195588149e-191
598.40808303232644e-201.68161660646529e-191
602.37348581048276e-204.74697162096552e-201
611.60824509322563e-203.21649018645125e-201
623.78243175135656e-217.56486350271313e-211
632.12533631081681e-194.25067262163362e-191
643.80346951377141e-197.60693902754282e-191
658.56304048513556e-181.71260809702711e-171
664.23808072281062e-178.47616144562125e-171
672.00442969784723e-154.00885939569446e-150.999999999999998
681.78616379756754e-143.57232759513508e-140.999999999999982
691.8965841185248e-143.7931682370496e-140.99999999999998
701.78188084897448e-133.56376169794897e-130.999999999999822
712.94484472716513e-135.88968945433026e-130.999999999999706
721.26748504590027e-132.53497009180054e-130.999999999999873
735.3230453131443e-141.06460906262886e-130.999999999999947
742.85210546919010e-145.70421093838021e-140.999999999999971
754.27336770328254e-148.54673540656509e-140.999999999999957
762.43189248751815e-144.8637849750363e-140.999999999999976
774.36949362829882e-148.73898725659765e-140.999999999999956
783.70946047655363e-147.41892095310726e-140.999999999999963
791.33393701045964e-132.66787402091928e-130.999999999999867
801.42229965515658e-122.84459931031316e-120.999999999998578
818.42132319830315e-131.68426463966063e-120.999999999999158
821.13361587130153e-122.26723174260306e-120.999999999998866
835.14545762706219e-131.02909152541244e-120.999999999999486
842.40445884284262e-134.80891768568524e-130.99999999999976
851.7262352601033e-133.4524705202066e-130.999999999999827
868.47076333903476e-141.69415266780695e-130.999999999999915
874.79401727094107e-149.58803454188215e-140.999999999999952
882.00763780660202e-144.01527561320404e-140.99999999999998
892.02296133366938e-144.04592266733876e-140.99999999999998
901.15141820603907e-142.30283641207814e-140.999999999999988
912.19225749858056e-144.38451499716112e-140.999999999999978
925.32896083186703e-141.06579216637341e-130.999999999999947
934.72273317372378e-149.44546634744756e-140.999999999999953
941.30452181753200e-132.60904363506399e-130.99999999999987
956.65209468115588e-141.33041893623118e-130.999999999999933
962.95898334328051e-135.91796668656101e-130.999999999999704
976.71889600726389e-131.34377920145278e-120.999999999999328
983.33121389980283e-136.66242779960566e-130.999999999999667
991.97780674055326e-133.95561348110652e-130.999999999999802
1001.65921781036832e-133.31843562073664e-130.999999999999834
1012.11624563176383e-134.23249126352766e-130.999999999999788
1021.35958359583488e-132.71916719166976e-130.999999999999864
1035.20307622889115e-131.04061524577823e-120.99999999999948
1046.20805589376538e-131.24161117875308e-120.99999999999938
1054.9437858827853e-139.8875717655706e-130.999999999999506
1064.83815006522327e-139.67630013044653e-130.999999999999516
1072.64650278502124e-135.29300557004248e-130.999999999999735
1083.89249591453678e-137.78499182907356e-130.99999999999961
1096.5963759864836e-131.31927519729672e-120.99999999999934
1101.80551768011680e-123.61103536023359e-120.999999999998195
1119.54811362085322e-131.90962272417064e-120.999999999999045
1124.74674401639808e-139.49348803279616e-130.999999999999525
1132.23185390792622e-134.46370781585244e-130.999999999999777
1141.20540600418994e-132.41081200837987e-130.99999999999988
1159.59336877342326e-141.91867375468465e-130.999999999999904
1164.61884065104327e-149.23768130208653e-140.999999999999954
1172.96682594854668e-145.93365189709337e-140.99999999999997
1181.04223138666480e-132.08446277332961e-130.999999999999896
1199.50967903739246e-141.90193580747849e-130.999999999999905
1209.5475346635977e-141.90950693271954e-130.999999999999905
1215.40388328782468e-141.08077665756494e-130.999999999999946
1224.05033679718842e-148.10067359437683e-140.99999999999996
1235.5707321599029e-141.11414643198058e-130.999999999999944
1243.63849524505239e-147.27699049010479e-140.999999999999964
1253.3053336048041e-146.6106672096082e-140.999999999999967
1261.63736700924160e-143.27473401848319e-140.999999999999984
1271.33610666292346e-142.67221332584693e-140.999999999999987
1286.60935313286634e-151.32187062657327e-140.999999999999993
1294.25992559212226e-158.51985118424451e-150.999999999999996
1303.77975009256245e-157.5595001851249e-150.999999999999996
1318.37442279490573e-141.67488455898115e-130.999999999999916
1321.90219792785771e-133.80439585571543e-130.99999999999981
1338.0227588862421e-131.60455177724842e-120.999999999999198
1341.69993624886529e-123.39987249773058e-120.9999999999983
1356.58622302312026e-121.31724460462405e-110.999999999993414
1361.32072683433539e-102.64145366867078e-100.999999999867927
1371.22641995495029e-092.45283990990058e-090.99999999877358
1381.95107568685006e-093.90215137370012e-090.999999998048924
1397.25717949984008e-091.45143589996802e-080.99999999274282
1401.55032084719504e-083.10064169439009e-080.999999984496792
1412.25789902030801e-084.51579804061602e-080.99999997742101
1423.25816426196389e-086.51632852392778e-080.999999967418357
1432.90280923171368e-085.80561846342736e-080.999999970971908
1442.94775996746386e-085.89551993492773e-080.9999999705224
1454.03697221245785e-088.0739444249157e-080.999999959630278
1462.26256948338941e-084.52513896677882e-080.999999977374305
1471.48306481412101e-082.96612962824201e-080.999999985169352
1481.08509180321529e-082.17018360643059e-080.999999989149082
1491.74001224656958e-083.48002449313917e-080.999999982599878
1502.42394274072340e-084.84788548144679e-080.999999975760573
1511.11506659574462e-072.23013319148924e-070.99999988849334
1522.61161362642186e-075.22322725284373e-070.999999738838637
1533.78163186232042e-077.56326372464085e-070.999999621836814
1546.16201653667139e-071.23240330733428e-060.999999383798346
1557.03562966720508e-071.40712593344102e-060.999999296437033
1561.00002580305371e-062.00005160610742e-060.999998999974197
1578.08677236035394e-071.61735447207079e-060.999999191322764
1588.00208492201118e-071.60041698440224e-060.999999199791508
1591.17507253018197e-062.35014506036394e-060.99999882492747
1609.42065418988267e-071.88413083797653e-060.999999057934581
1611.47419520981919e-062.94839041963838e-060.99999852580479
1622.53386343851803e-065.06772687703607e-060.999997466136561
1631.07326358467037e-052.14652716934074e-050.999989267364153
1642.66190733678372e-055.32381467356745e-050.999973380926632
1653.16882924828982e-056.33765849657964e-050.999968311707517
1665.50800759168271e-050.0001101601518336540.999944919924083
1677.72361789337881e-050.0001544723578675760.999922763821066
1680.0001417230062208230.0002834460124416460.99985827699378
1690.0001612568151259660.0003225136302519330.999838743184874
1700.0003338787590500450.000667757518100090.99966612124095
1710.000634541095924380.001269082191848760.999365458904076
1720.0004774301316564850.000954860263312970.999522569868344
1730.0005607072164861520.001121414432972300.999439292783514
1740.000592194458715660.001184388917431320.999407805541284
1750.001239280168574810.002478560337149620.998760719831425
1760.002159408503191080.004318817006382150.99784059149681
1770.002165172339089680.004330344678179350.99783482766091
1780.003624341204345220.007248682408690450.996375658795655
1790.003499859957772080.006999719915544170.996500140042228
1800.003049667081097520.006099334162195030.996950332918902
1810.00254491558479610.00508983116959220.997455084415204
1820.002318972364120720.004637944728241440.99768102763588
1830.001521218395541830.003042436791083670.998478781604458
1840.001221674539692590.002443349079385180.998778325460307
1850.0008892020397800040.001778404079560010.99911079796022
1860.0006603039909904890.001320607981980980.99933969600901
1870.0007155123409394940.001431024681878990.99928448765906
1880.0005655209697132270.001131041939426450.999434479030287
1890.0003440674121240370.0006881348242480740.999655932587876
1900.0002231206385411450.000446241277082290.99977687936146
1910.0001504598417605440.0003009196835210880.99984954015824
1929.63589849091027e-050.0001927179698182050.99990364101509
1938.78637575049426e-050.0001757275150098850.999912136242495
1949.67131993851262e-050.0001934263987702520.999903286800615
1950.0001133876459181500.0002267752918363010.999886612354082
1960.0007214156618651190.001442831323730240.999278584338135
1970.00147024615624990.00294049231249980.99852975384375
1980.004746848600312140.009493697200624280.995253151399688
1990.004806089464075440.009612178928150870.995193910535925
2000.003929144713402990.007858289426805990.996070855286597
2010.004382908317664470.008765816635328940.995617091682335
2020.004671701436424040.009343402872848080.995328298563576
2030.005842241136376790.01168448227275360.994157758863623
2040.005860349547564170.01172069909512830.994139650452436
2050.006606103970767420.01321220794153480.993393896029233
2060.007008286578867870.01401657315773570.992991713421132
2070.006827123115727770.01365424623145550.993172876884272
2080.9530431062277990.09391378754440280.0469568937722014







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1820.952879581151832NOK
5% type I error level1900.99476439790576NOK
10% type I error level1911NOK

\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 & 182 & 0.952879581151832 & NOK \tabularnewline
5% type I error level & 190 & 0.99476439790576 & NOK \tabularnewline
10% type I error level & 191 & 1 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101643&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]182[/C][C]0.952879581151832[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]190[/C][C]0.99476439790576[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]191[/C][C]1[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101643&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101643&T=6

As an alternative you can also use a QR Code:  

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 level1820.952879581151832NOK
5% type I error level1900.99476439790576NOK
10% type I error level1911NOK



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 2 ; par2 = Include Monthly Dummies ; par3 = No 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')
}