Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationThu, 06 Dec 2012 13:11:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/06/t1354817571qpyq1mxm6supzt6.htm/, Retrieved Fri, 29 Mar 2024 04:56:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197196, Retrieved Fri, 29 Mar 2024 04:56:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R PD    [Recursive Partitioning (Regression Trees)] [] [2012-12-06 18:11:51] [195a7509fef65339447329cdcf8835cc] [Current]
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Dataseries X:
56	396	81	3	79	30	115
56	297	55	4	58	28	109
54	559	50	12	60	38	146
89	967	125	2	108	30	116
40	270	40	1	49	22	68
25	143	37	3	0	26	101
92	1562	63	0	121	25	96
18	109	44	0	1	18	67
63	371	88	0	20	11	44
44	656	66	5	43	26	100
33	511	57	0	69	25	93
84	655	74	0	78	38	140
88	465	49	7	86	44	166
55	525	52	7	44	30	99
60	885	88	3	104	40	139
66	497	36	9	63	34	130
154	1436	108	0	158	47	181
53	612	43	4	102	30	116
119	865	75	3	77	31	116
41	385	32	0	82	23	88
61	567	44	7	115	36	139
58	639	85	0	101	36	135
75	963	86	1	80	30	108
33	398	56	5	50	25	89
40	410	50	7	83	39	156
92	966	135	0	123	34	129
100	801	63	0	73	31	118
112	892	81	5	81	31	118
73	513	52	0	105	33	125
40	469	44	0	47	25	95
45	683	113	0	105	33	126
60	643	39	3	94	35	135
62	535	73	4	44	42	154
75	625	48	1	114	43	165
31	264	33	4	38	30	113
77	992	59	2	107	33	127
34	238	41	0	30	13	52
46	818	69	0	71	32	121
99	937	64	0	84	36	136
17	70	1	0	0	0	0
66	507	59	2	59	28	108
30	260	32	1	33	14	46
76	503	129	0	42	17	54
146	927	37	2	96	32	124
67	1269	31	10	106	30	115
56	537	65	6	56	35	128
107	910	107	0	57	20	80
58	532	74	5	59	28	97
34	345	54	4	39	28	104
61	918	76	1	34	39	59
119	1635	715	2	76	34	125
42	330	57	2	20	26	82
66	557	66	0	91	39	149
89	1178	106	8	115	39	149
44	740	54	3	85	33	122
66	452	32	0	76	28	118
24	218	20	0	8	4	12
259	764	71	8	79	39	144
17	255	21	5	21	18	67
64	454	70	3	30	14	52
41	866	112	1	76	29	108
68	574	66	5	101	44	166
168	1276	190	1	94	21	80
43	379	66	1	27	16	60
132	825	165	5	92	28	107
105	798	56	0	123	35	127
71	663	61	12	75	28	107
112	1069	53	8	128	38	146
94	921	127	8	105	23	84
82	858	63	8	55	36	141
70	711	38	8	56	32	123
57	503	50	2	41	29	111
53	382	52	0	72	25	98
103	464	42	5	67	27	105
121	717	76	8	75	36	135
62	690	67	2	114	28	107
52	462	50	5	118	23	85
52	657	53	12	77	40	155
32	385	39	6	22	23	88
62	577	50	7	66	40	155
45	619	77	2	69	28	104
46	479	57	0	105	34	132
63	817	73	4	116	33	127
75	752	34	3	88	28	108
88	430	39	6	73	34	129
46	451	46	2	99	30	116
53	537	63	0	62	33	122
37	519	35	1	53	22	85
90	1000	106	0	118	38	147
63	637	43	5	30	26	99
78	465	47	2	100	35	87
25	437	31	0	49	8	28
45	711	162	0	24	24	90
46	299	57	5	67	29	109
41	248	36	0	46	20	78
144	1162	263	1	57	29	111
82	714	78	0	75	45	158
91	905	63	1	135	37	141
71	649	54	1	68	33	122
63	512	63	2	124	33	124
53	472	77	6	33	25	93
62	905	79	1	98	32	124
63	786	110	4	58	29	112
32	489	56	2	68	28	108
39	479	56	3	81	28	99
62	617	43	0	131	31	117
117	925	111	10	110	52	199
34	351	71	0	37	21	78
92	1144	62	9	130	24	91
93	669	56	7	93	41	158
54	707	74	0	118	33	126
144	458	60	0	39	32	122
14	214	43	4	13	19	71
61	599	68	4	74	20	75
109	572	53	0	81	31	115
38	897	87	0	109	31	119
73	819	46	0	151	32	124
75	720	105	1	51	18	72
50	273	32	0	28	23	91
61	508	133	1	40	17	45
55	506	79	0	56	20	78
77	451	51	0	27	12	39
75	699	207	4	37	17	68
72	407	67	0	83	30	119
50	465	47	4	54	31	117
32	245	34	4	27	10	39
53	370	66	3	28	13	50
42	316	76	0	59	22	88
71	603	65	0	133	42	155
10	154	9	0	12	1	0
35	229	42	5	0	9	36
65	577	45	0	106	32	123
25	192	25	4	23	11	32
66	617	115	0	44	25	99
41	411	97	0	71	36	136
86	975	53	1	116	31	117
16	146	2	0	4	0	0
42	705	52	5	62	24	88
19	184	44	0	12	13	39
19	200	22	0	18	8	25
45	274	35	0	14	13	52
65	502	74	0	60	19	75
35	382	103	0	7	18	71
95	964	144	2	98	33	124
49	537	60	7	64	40	151
37	438	134	1	29	22	71
64	369	89	8	32	38	145
38	417	42	2	25	24	87
34	276	52	0	16	8	27
32	514	98	2	48	35	131
65	822	99	0	100	43	162
52	389	52	0	46	43	165
62	466	29	1	45	14	54
65	1255	125	3	129	41	159
83	694	106	0	130	38	147
95	1024	95	3	136	45	170
29	400	40	0	59	31	119
18	397	140	0	25	13	49
33	350	43	0	32	28	104
247	719	128	4	63	31	120
139	1277	142	4	95	40	150
29	356	73	11	14	30	112
118	457	72	0	36	16	59
110	1402	128	0	113	37	136
67	600	61	4	47	30	107
42	480	73	0	92	35	130
65	595	148	1	70	32	115
94	436	64	0	19	27	107
64	230	45	0	50	20	75
81	651	58	0	41	18	71
95	1367	97	9	91	31	120
67	564	50	1	111	31	116
63	716	37	3	41	21	79
83	747	50	10	120	39	150
45	467	105	5	135	41	156
30	671	69	0	27	13	51
70	861	46	2	87	32	118
32	319	57	0	25	18	71
83	612	52	1	131	39	144
31	433	98	2	45	14	47
67	434	61	4	29	7	28
66	503	89	0	58	17	68
10	85	0	0	4	0	0
70	564	48	2	47	30	110
103	824	91	1	109	37	147
5	74	0	0	7	0	0
20	259	7	0	12	5	15
5	69	3	0	0	1	4
36	535	54	1	37	16	64
34	239	70	0	37	32	111
48	438	36	2	46	24	85
40	459	37	0	15	17	68
43	426	123	3	42	11	40
31	288	247	6	7	24	80
42	498	46	0	54	22	88
46	454	72	2	54	12	48
33	376	41	0	14	19	76
18	225	24	2	16	13	51
55	555	45	1	33	17	67
35	252	33	1	32	15	59
59	208	27	2	21	16	61
19	130	36	1	15	24	76
66	481	87	0	38	15	60
60	389	90	1	22	17	68
36	565	114	3	28	18	71
25	173	31	0	10	20	76
47	278	45	0	31	16	62
54	609	69	0	32	16	61
53	422	51	0	32	18	67
40	445	34	1	43	22	88
40	387	60	4	27	8	30
39	339	45	0	37	17	64
14	181	54	0	20	18	68
45	245	25	0	32	16	64
36	384	38	7	0	23	91
28	212	52	2	5	22	88
44	399	67	0	26	13	52
30	229	74	7	10	13	49
22	224	38	3	27	16	62
17	203	30	0	11	16	61
31	333	26	0	29	20	76
55	384	67	6	25	22	88
54	636	132	2	55	17	66
21	185	42	0	23	18	71
14	93	35	0	5	17	68
81	581	118	3	43	12	48
35	248	68	0	23	7	25
43	304	43	1	34	17	68
46	344	76	1	36	14	41
30	407	64	0	35	23	90
23	170	48	1	0	17	66
38	312	64	0	37	14	54
54	507	56	0	28	15	59
20	224	71	0	16	17	60
53	340	75	0	26	21	77
45	168	39	0	38	18	68
39	443	42	0	23	18	72
20	204	39	0	22	17	67
24	367	93	0	30	17	64
31	210	38	0	16	16	63
35	335	60	0	18	15	59
151	364	71	0	28	21	84
52	178	52	0	32	16	64
30	206	27	2	21	14	56
31	279	59	0	23	15	54
29	387	40	1	29	17	67
57	490	79	1	50	15	58
40	238	44	0	12	15	59
44	343	65	0	21	10	40
25	232	10	0	18	6	22
77	530	124	0	27	22	83
35	291	81	0	41	21	81
11	67	15	0	13	1	2
63	397	92	1	12	18	72
44	467	42	0	21	17	61
19	178	10	0	8	4	15
13	175	24	0	26	10	32
42	299	64	0	27	16	62
38	154	45	1	13	16	58
29	106	22	0	16	9	36
20	189	56	0	2	16	59
27	194	94	0	42	17	68
20	135	19	0	5	7	21
19	201	35	0	37	15	55
37	207	32	0	17	14	54
26	280	35	0	38	14	55
42	260	48	0	37	18	72
49	227	49	0	29	12	41
30	239	48	0	32	16	61
49	333	62	0	35	21	67
67	428	96	1	17	19	76
28	230	45	0	20	16	64
19	292	63	0	7	1	3
49	350	71	1	46	16	63
27	186	26	0	24	10	40
30	326	48	6	40	19	69
22	155	29	3	3	12	48
12	75	19	1	10	2	8
31	361	45	2	37	14	52
20	261	45	0	17	17	66
20	299	67	0	28	19	76
39	300	30	0	19	14	43
29	450	36	3	29	11	39
16	183	34	1	8	4	14
27	238	36	0	10	16	61
21	165	34	0	15	20	71
19	234	37	1	15	12	44
35	176	46	0	28	15	60
14	329	44	0	17	16	64




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197196&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197196&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197196&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 time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Goodness of Fit
Correlation0.9819
R-squared0.9641
RMSE7.6041

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.9819 \tabularnewline
R-squared & 0.9641 \tabularnewline
RMSE & 7.6041 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197196&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.9819[/C][/ROW]
[ROW][C]R-squared[/C][C]0.9641[/C][/ROW]
[ROW][C]RMSE[/C][C]7.6041[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197196&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197196&T=1

As an alternative you can also use a QR Code:  

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

Goodness of Fit
Correlation0.9819
R-squared0.9641
RMSE7.6041







Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
1115111.5882352941183.41176470588235
2109106.1333333333332.86666666666666
3146141.4074074074074.59259259259258
4116111.5882352941184.41176470588235
56885.2608695652174-17.2608695652174
6101956
796951
86770-3
94440.3753.625
10100955
119395-2
12140141.407407407407-1.40740740740742
13166165.2857142857140.714285714285722
1499111.588235294118-12.5882352941177
15139141.407407407407-2.40740740740742
16130121.9767441860478.02325581395348
17181165.28571428571415.7142857142857
18116111.5882352941184.41176470588235
19116121.976744186047-5.97674418604652
208885.26086956521742.73913043478261
21139141.407407407407-2.40740740740742
22135141.407407407407-6.40740740740742
23108111.588235294118-3.58823529411765
248995-6
25156141.40740740740714.5925925925926
26129121.9767441860477.02325581395348
27118121.976744186047-3.97674418604652
28118121.976744186047-3.97674418604652
29125121.9767441860473.02325581395348
3095950
31126121.9767441860474.02325581395348
32135121.97674418604713.0232558139535
33154165.285714285714-11.2857142857143
34165165.285714285714-0.285714285714278
35113111.5882352941181.41176470588235
36127121.9767441860475.02325581395348
375249.952.05
38121121.976744186047-0.976744186046517
39136141.407407407407-5.40740740740742
4005.61538461538461-5.61538461538461
41108106.1333333333331.86666666666666
424649.95-3.95
435463.0526315789474-9.05263157894737
44124121.9767441860472.02325581395348
45115111.5882352941183.41176470588235
46128121.9767441860476.02325581395348
478076.09523809523813.9047619047619
4897106.133333333333-9.13333333333334
49104106.133333333333-2.13333333333334
5059141.407407407407-82.4074074074074
51125121.9767441860473.02325581395348
528295-13
53149141.4074074074077.59259259259258
54149141.4074074074077.59259259259258
55122121.9767441860470.0232558139534831
56118106.13333333333311.8666666666667
57125.615384615384616.38461538461539
58144141.4074074074072.59259259259258
596770-3
605249.952.05
61108111.588235294118-3.58823529411765
62166165.2857142857140.714285714285722
638076.09523809523813.9047619047619
646063.0526315789474-3.05263157894737
65107106.1333333333330.86666666666666
66127121.9767441860475.02325581395348
67107106.1333333333330.86666666666666
68146141.4074074074074.59259259259258
698485.2608695652174-1.26086956521739
70141141.407407407407-0.407407407407419
71123121.9767441860471.02325581395348
72111111.588235294118-0.588235294117652
7398953
74105106.133333333333-1.13333333333334
75135141.407407407407-6.40740740740742
76107106.1333333333330.86666666666666
778585.2608695652174-0.260869565217391
78155141.40740740740713.5925925925926
798885.26086956521742.73913043478261
80155141.40740740740713.5925925925926
81104106.133333333333-2.13333333333334
82132121.97674418604710.0232558139535
83127121.9767441860475.02325581395348
84108106.1333333333331.86666666666666
85129121.9767441860477.02325581395348
86116111.5882352941184.41176470588235
87122121.9767441860470.0232558139534831
888585.2608695652174-0.260869565217391
89147141.4074074074075.59259259259258
9099954
9187121.976744186047-34.9767441860465
922825.752.25
939085.26086956521744.73913043478261
94109111.588235294118-2.58823529411765
957876.09523809523811.9047619047619
96111111.588235294118-0.588235294117652
97158165.285714285714-7.28571428571428
98141141.407407407407-0.407407407407419
99122121.9767441860470.0232558139534831
100124121.9767441860472.02325581395348
1019395-2
102124121.9767441860472.02325581395348
103112111.5882352941180.411764705882348
104108106.1333333333331.86666666666666
10599106.133333333333-7.13333333333334
106117121.976744186047-4.97674418604652
107199165.28571428571433.7142857142857
1087876.09523809523811.9047619047619
1099185.26086956521745.73913043478261
110158165.285714285714-7.28571428571428
111126121.9767441860474.02325581395348
112122121.9767441860470.0232558139534831
1137176.0952380952381-5.0952380952381
1147576.0952380952381-1.0952380952381
115115121.976744186047-6.97674418604652
116119121.976744186047-2.97674418604652
117124121.9767441860472.02325581395348
11872702
1199185.26086956521745.73913043478261
1204563.0526315789474-18.0526315789474
1217876.09523809523811.9047619047619
1223940.375-1.375
1236863.05263157894744.94736842105263
124119111.5882352941187.41176470588235
125117121.976744186047-4.97674418604652
1263940.375-1.375
1275049.950.0499999999999972
1288885.26086956521742.73913043478261
129155165.285714285714-10.2857142857143
13005.61538461538461-5.61538461538461
1313640.375-4.375
132123121.9767441860471.02325581395348
1333240.375-8.375
13499954
135136141.407407407407-5.40740740740742
136117121.976744186047-4.97674418604652
13705.61538461538461-5.61538461538461
1388885.26086956521742.73913043478261
1393949.95-10.95
1402525.75-0.75
1415249.952.05
1427576.0952380952381-1.0952380952381
14371701
144124121.9767441860472.02325581395348
145151141.4074074074079.59259259259258
1467185.2608695652174-14.2608695652174
147145141.4074074074073.59259259259258
1488785.26086956521741.73913043478261
1492725.751.25
150131121.9767441860479.02325581395348
151162165.285714285714-3.28571428571428
152165165.285714285714-0.285714285714278
1535449.954.05
154159165.285714285714-6.28571428571428
155147141.4074074074075.59259259259258
156170165.2857142857144.71428571428572
157119121.976744186047-2.97674418604652
1584949.95-0.950000000000003
159104106.133333333333-2.13333333333334
160120121.976744186047-1.97674418604652
161150141.4074074074078.59259259259258
162112111.5882352941180.411764705882348
1635963.0526315789474-4.05263157894737
164136141.407407407407-5.40740740740742
165107111.588235294118-4.58823529411765
166130121.9767441860478.02325581395348
167115121.976744186047-6.97674418604652
168107106.1333333333330.86666666666666
1697576.0952380952381-1.0952380952381
17071701
171120121.976744186047-1.97674418604652
172116121.976744186047-5.97674418604652
1737976.09523809523812.9047619047619
174150141.4074074074078.59259259259258
175156165.285714285714-9.28571428571428
1765149.951.05
177118121.976744186047-3.97674418604652
17871701
179144141.4074074074072.59259259259258
1804749.95-2.95
1812825.752.25
1826863.05263157894744.94736842105263
18305.61538461538461-5.61538461538461
184110111.588235294118-1.58823529411765
185147141.4074074074075.59259259259258
18605.61538461538461-5.61538461538461
187155.615384615384619.38461538461539
18845.61538461538461-1.61538461538461
1896463.05263157894740.94736842105263
190111121.976744186047-10.9767441860465
1918585.2608695652174-0.260869565217391
1926863.05263157894744.94736842105263
1934040.375-0.375
1948085.2608695652174-5.26086956521739
1958885.26086956521742.73913043478261
1964840.3757.625
1977676.0952380952381-0.095238095238102
1985149.951.05
1996763.05263157894743.94736842105263
2005958.11111111111110.888888888888886
2016163.0526315789474-2.05263157894737
2027685.2608695652174-9.26086956521739
2036058.11111111111111.88888888888889
2046863.05263157894744.94736842105263
20571701
2067676.0952380952381-0.095238095238102
2076263.0526315789474-1.05263157894737
2086163.0526315789474-2.05263157894737
2096770-3
2108885.26086956521742.73913043478261
2113025.754.25
2126463.05263157894740.94736842105263
2136870-2
2146463.05263157894740.94736842105263
2159185.26086956521745.73913043478261
2168885.26086956521742.73913043478261
2175249.952.05
2184949.95-0.950000000000003
2196263.0526315789474-1.05263157894737
2206163.0526315789474-2.05263157894737
2217676.0952380952381-0.095238095238102
2228885.26086956521742.73913043478261
2236663.05263157894742.94736842105263
22471701
2256863.05263157894744.94736842105263
2264840.3757.625
2272525.75-0.75
2286863.05263157894744.94736842105263
2294149.95-8.95
2309085.26086956521744.73913043478261
2316663.05263157894742.94736842105263
2325449.954.05
2335958.11111111111110.888888888888886
2346063.0526315789474-3.05263157894737
2357776.09523809523810.904761904761898
2366870-2
23772702
2386763.05263157894743.94736842105263
2396463.05263157894740.94736842105263
2406363.0526315789474-0.0526315789473699
2415958.11111111111110.888888888888886
2428476.09523809523817.9047619047619
2436463.05263157894740.94736842105263
2445649.956.05
2455458.1111111111111-4.11111111111111
2466763.05263157894743.94736842105263
2475858.1111111111111-0.111111111111114
2485958.11111111111110.888888888888886
2494040.375-0.375
2502225.75-3.75
2518385.2608695652174-2.26086956521739
2528176.09523809523814.9047619047619
25325.61538461538461-3.61538461538461
25472702
2556163.0526315789474-2.05263157894737
256155.615384615384619.38461538461539
2573240.375-8.375
2586263.0526315789474-1.05263157894737
2595863.0526315789474-5.05263157894737
2603640.375-4.375
2615963.0526315789474-4.05263157894737
2626863.05263157894744.94736842105263
2632125.75-4.75
2645558.1111111111111-3.11111111111111
2655449.954.05
2665549.955.05
26772702
2684140.3750.625
2696163.0526315789474-2.05263157894737
2706776.0952380952381-9.0952380952381
2717676.0952380952381-0.095238095238102
2726463.05263157894740.94736842105263
27335.61538461538461-2.61538461538461
2746363.0526315789474-0.0526315789473699
2754040.375-0.375
2766976.0952380952381-7.0952380952381
2774840.3757.625
27885.615384615384612.38461538461539
2795249.952.05
2806663.05263157894742.94736842105263
2817676.0952380952381-0.095238095238102
2824349.95-6.95
2833940.375-1.375
284145.615384615384618.38461538461539
2856163.0526315789474-2.05263157894737
2867176.0952380952381-5.0952380952381
2874440.3753.625
2886058.11111111111111.88888888888889
2896463.05263157894740.94736842105263

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 115 & 111.588235294118 & 3.41176470588235 \tabularnewline
2 & 109 & 106.133333333333 & 2.86666666666666 \tabularnewline
3 & 146 & 141.407407407407 & 4.59259259259258 \tabularnewline
4 & 116 & 111.588235294118 & 4.41176470588235 \tabularnewline
5 & 68 & 85.2608695652174 & -17.2608695652174 \tabularnewline
6 & 101 & 95 & 6 \tabularnewline
7 & 96 & 95 & 1 \tabularnewline
8 & 67 & 70 & -3 \tabularnewline
9 & 44 & 40.375 & 3.625 \tabularnewline
10 & 100 & 95 & 5 \tabularnewline
11 & 93 & 95 & -2 \tabularnewline
12 & 140 & 141.407407407407 & -1.40740740740742 \tabularnewline
13 & 166 & 165.285714285714 & 0.714285714285722 \tabularnewline
14 & 99 & 111.588235294118 & -12.5882352941177 \tabularnewline
15 & 139 & 141.407407407407 & -2.40740740740742 \tabularnewline
16 & 130 & 121.976744186047 & 8.02325581395348 \tabularnewline
17 & 181 & 165.285714285714 & 15.7142857142857 \tabularnewline
18 & 116 & 111.588235294118 & 4.41176470588235 \tabularnewline
19 & 116 & 121.976744186047 & -5.97674418604652 \tabularnewline
20 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
21 & 139 & 141.407407407407 & -2.40740740740742 \tabularnewline
22 & 135 & 141.407407407407 & -6.40740740740742 \tabularnewline
23 & 108 & 111.588235294118 & -3.58823529411765 \tabularnewline
24 & 89 & 95 & -6 \tabularnewline
25 & 156 & 141.407407407407 & 14.5925925925926 \tabularnewline
26 & 129 & 121.976744186047 & 7.02325581395348 \tabularnewline
27 & 118 & 121.976744186047 & -3.97674418604652 \tabularnewline
28 & 118 & 121.976744186047 & -3.97674418604652 \tabularnewline
29 & 125 & 121.976744186047 & 3.02325581395348 \tabularnewline
30 & 95 & 95 & 0 \tabularnewline
31 & 126 & 121.976744186047 & 4.02325581395348 \tabularnewline
32 & 135 & 121.976744186047 & 13.0232558139535 \tabularnewline
33 & 154 & 165.285714285714 & -11.2857142857143 \tabularnewline
34 & 165 & 165.285714285714 & -0.285714285714278 \tabularnewline
35 & 113 & 111.588235294118 & 1.41176470588235 \tabularnewline
36 & 127 & 121.976744186047 & 5.02325581395348 \tabularnewline
37 & 52 & 49.95 & 2.05 \tabularnewline
38 & 121 & 121.976744186047 & -0.976744186046517 \tabularnewline
39 & 136 & 141.407407407407 & -5.40740740740742 \tabularnewline
40 & 0 & 5.61538461538461 & -5.61538461538461 \tabularnewline
41 & 108 & 106.133333333333 & 1.86666666666666 \tabularnewline
42 & 46 & 49.95 & -3.95 \tabularnewline
43 & 54 & 63.0526315789474 & -9.05263157894737 \tabularnewline
44 & 124 & 121.976744186047 & 2.02325581395348 \tabularnewline
45 & 115 & 111.588235294118 & 3.41176470588235 \tabularnewline
46 & 128 & 121.976744186047 & 6.02325581395348 \tabularnewline
47 & 80 & 76.0952380952381 & 3.9047619047619 \tabularnewline
48 & 97 & 106.133333333333 & -9.13333333333334 \tabularnewline
49 & 104 & 106.133333333333 & -2.13333333333334 \tabularnewline
50 & 59 & 141.407407407407 & -82.4074074074074 \tabularnewline
51 & 125 & 121.976744186047 & 3.02325581395348 \tabularnewline
52 & 82 & 95 & -13 \tabularnewline
53 & 149 & 141.407407407407 & 7.59259259259258 \tabularnewline
54 & 149 & 141.407407407407 & 7.59259259259258 \tabularnewline
55 & 122 & 121.976744186047 & 0.0232558139534831 \tabularnewline
56 & 118 & 106.133333333333 & 11.8666666666667 \tabularnewline
57 & 12 & 5.61538461538461 & 6.38461538461539 \tabularnewline
58 & 144 & 141.407407407407 & 2.59259259259258 \tabularnewline
59 & 67 & 70 & -3 \tabularnewline
60 & 52 & 49.95 & 2.05 \tabularnewline
61 & 108 & 111.588235294118 & -3.58823529411765 \tabularnewline
62 & 166 & 165.285714285714 & 0.714285714285722 \tabularnewline
63 & 80 & 76.0952380952381 & 3.9047619047619 \tabularnewline
64 & 60 & 63.0526315789474 & -3.05263157894737 \tabularnewline
65 & 107 & 106.133333333333 & 0.86666666666666 \tabularnewline
66 & 127 & 121.976744186047 & 5.02325581395348 \tabularnewline
67 & 107 & 106.133333333333 & 0.86666666666666 \tabularnewline
68 & 146 & 141.407407407407 & 4.59259259259258 \tabularnewline
69 & 84 & 85.2608695652174 & -1.26086956521739 \tabularnewline
70 & 141 & 141.407407407407 & -0.407407407407419 \tabularnewline
71 & 123 & 121.976744186047 & 1.02325581395348 \tabularnewline
72 & 111 & 111.588235294118 & -0.588235294117652 \tabularnewline
73 & 98 & 95 & 3 \tabularnewline
74 & 105 & 106.133333333333 & -1.13333333333334 \tabularnewline
75 & 135 & 141.407407407407 & -6.40740740740742 \tabularnewline
76 & 107 & 106.133333333333 & 0.86666666666666 \tabularnewline
77 & 85 & 85.2608695652174 & -0.260869565217391 \tabularnewline
78 & 155 & 141.407407407407 & 13.5925925925926 \tabularnewline
79 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
80 & 155 & 141.407407407407 & 13.5925925925926 \tabularnewline
81 & 104 & 106.133333333333 & -2.13333333333334 \tabularnewline
82 & 132 & 121.976744186047 & 10.0232558139535 \tabularnewline
83 & 127 & 121.976744186047 & 5.02325581395348 \tabularnewline
84 & 108 & 106.133333333333 & 1.86666666666666 \tabularnewline
85 & 129 & 121.976744186047 & 7.02325581395348 \tabularnewline
86 & 116 & 111.588235294118 & 4.41176470588235 \tabularnewline
87 & 122 & 121.976744186047 & 0.0232558139534831 \tabularnewline
88 & 85 & 85.2608695652174 & -0.260869565217391 \tabularnewline
89 & 147 & 141.407407407407 & 5.59259259259258 \tabularnewline
90 & 99 & 95 & 4 \tabularnewline
91 & 87 & 121.976744186047 & -34.9767441860465 \tabularnewline
92 & 28 & 25.75 & 2.25 \tabularnewline
93 & 90 & 85.2608695652174 & 4.73913043478261 \tabularnewline
94 & 109 & 111.588235294118 & -2.58823529411765 \tabularnewline
95 & 78 & 76.0952380952381 & 1.9047619047619 \tabularnewline
96 & 111 & 111.588235294118 & -0.588235294117652 \tabularnewline
97 & 158 & 165.285714285714 & -7.28571428571428 \tabularnewline
98 & 141 & 141.407407407407 & -0.407407407407419 \tabularnewline
99 & 122 & 121.976744186047 & 0.0232558139534831 \tabularnewline
100 & 124 & 121.976744186047 & 2.02325581395348 \tabularnewline
101 & 93 & 95 & -2 \tabularnewline
102 & 124 & 121.976744186047 & 2.02325581395348 \tabularnewline
103 & 112 & 111.588235294118 & 0.411764705882348 \tabularnewline
104 & 108 & 106.133333333333 & 1.86666666666666 \tabularnewline
105 & 99 & 106.133333333333 & -7.13333333333334 \tabularnewline
106 & 117 & 121.976744186047 & -4.97674418604652 \tabularnewline
107 & 199 & 165.285714285714 & 33.7142857142857 \tabularnewline
108 & 78 & 76.0952380952381 & 1.9047619047619 \tabularnewline
109 & 91 & 85.2608695652174 & 5.73913043478261 \tabularnewline
110 & 158 & 165.285714285714 & -7.28571428571428 \tabularnewline
111 & 126 & 121.976744186047 & 4.02325581395348 \tabularnewline
112 & 122 & 121.976744186047 & 0.0232558139534831 \tabularnewline
113 & 71 & 76.0952380952381 & -5.0952380952381 \tabularnewline
114 & 75 & 76.0952380952381 & -1.0952380952381 \tabularnewline
115 & 115 & 121.976744186047 & -6.97674418604652 \tabularnewline
116 & 119 & 121.976744186047 & -2.97674418604652 \tabularnewline
117 & 124 & 121.976744186047 & 2.02325581395348 \tabularnewline
118 & 72 & 70 & 2 \tabularnewline
119 & 91 & 85.2608695652174 & 5.73913043478261 \tabularnewline
120 & 45 & 63.0526315789474 & -18.0526315789474 \tabularnewline
121 & 78 & 76.0952380952381 & 1.9047619047619 \tabularnewline
122 & 39 & 40.375 & -1.375 \tabularnewline
123 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
124 & 119 & 111.588235294118 & 7.41176470588235 \tabularnewline
125 & 117 & 121.976744186047 & -4.97674418604652 \tabularnewline
126 & 39 & 40.375 & -1.375 \tabularnewline
127 & 50 & 49.95 & 0.0499999999999972 \tabularnewline
128 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
129 & 155 & 165.285714285714 & -10.2857142857143 \tabularnewline
130 & 0 & 5.61538461538461 & -5.61538461538461 \tabularnewline
131 & 36 & 40.375 & -4.375 \tabularnewline
132 & 123 & 121.976744186047 & 1.02325581395348 \tabularnewline
133 & 32 & 40.375 & -8.375 \tabularnewline
134 & 99 & 95 & 4 \tabularnewline
135 & 136 & 141.407407407407 & -5.40740740740742 \tabularnewline
136 & 117 & 121.976744186047 & -4.97674418604652 \tabularnewline
137 & 0 & 5.61538461538461 & -5.61538461538461 \tabularnewline
138 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
139 & 39 & 49.95 & -10.95 \tabularnewline
140 & 25 & 25.75 & -0.75 \tabularnewline
141 & 52 & 49.95 & 2.05 \tabularnewline
142 & 75 & 76.0952380952381 & -1.0952380952381 \tabularnewline
143 & 71 & 70 & 1 \tabularnewline
144 & 124 & 121.976744186047 & 2.02325581395348 \tabularnewline
145 & 151 & 141.407407407407 & 9.59259259259258 \tabularnewline
146 & 71 & 85.2608695652174 & -14.2608695652174 \tabularnewline
147 & 145 & 141.407407407407 & 3.59259259259258 \tabularnewline
148 & 87 & 85.2608695652174 & 1.73913043478261 \tabularnewline
149 & 27 & 25.75 & 1.25 \tabularnewline
150 & 131 & 121.976744186047 & 9.02325581395348 \tabularnewline
151 & 162 & 165.285714285714 & -3.28571428571428 \tabularnewline
152 & 165 & 165.285714285714 & -0.285714285714278 \tabularnewline
153 & 54 & 49.95 & 4.05 \tabularnewline
154 & 159 & 165.285714285714 & -6.28571428571428 \tabularnewline
155 & 147 & 141.407407407407 & 5.59259259259258 \tabularnewline
156 & 170 & 165.285714285714 & 4.71428571428572 \tabularnewline
157 & 119 & 121.976744186047 & -2.97674418604652 \tabularnewline
158 & 49 & 49.95 & -0.950000000000003 \tabularnewline
159 & 104 & 106.133333333333 & -2.13333333333334 \tabularnewline
160 & 120 & 121.976744186047 & -1.97674418604652 \tabularnewline
161 & 150 & 141.407407407407 & 8.59259259259258 \tabularnewline
162 & 112 & 111.588235294118 & 0.411764705882348 \tabularnewline
163 & 59 & 63.0526315789474 & -4.05263157894737 \tabularnewline
164 & 136 & 141.407407407407 & -5.40740740740742 \tabularnewline
165 & 107 & 111.588235294118 & -4.58823529411765 \tabularnewline
166 & 130 & 121.976744186047 & 8.02325581395348 \tabularnewline
167 & 115 & 121.976744186047 & -6.97674418604652 \tabularnewline
168 & 107 & 106.133333333333 & 0.86666666666666 \tabularnewline
169 & 75 & 76.0952380952381 & -1.0952380952381 \tabularnewline
170 & 71 & 70 & 1 \tabularnewline
171 & 120 & 121.976744186047 & -1.97674418604652 \tabularnewline
172 & 116 & 121.976744186047 & -5.97674418604652 \tabularnewline
173 & 79 & 76.0952380952381 & 2.9047619047619 \tabularnewline
174 & 150 & 141.407407407407 & 8.59259259259258 \tabularnewline
175 & 156 & 165.285714285714 & -9.28571428571428 \tabularnewline
176 & 51 & 49.95 & 1.05 \tabularnewline
177 & 118 & 121.976744186047 & -3.97674418604652 \tabularnewline
178 & 71 & 70 & 1 \tabularnewline
179 & 144 & 141.407407407407 & 2.59259259259258 \tabularnewline
180 & 47 & 49.95 & -2.95 \tabularnewline
181 & 28 & 25.75 & 2.25 \tabularnewline
182 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
183 & 0 & 5.61538461538461 & -5.61538461538461 \tabularnewline
184 & 110 & 111.588235294118 & -1.58823529411765 \tabularnewline
185 & 147 & 141.407407407407 & 5.59259259259258 \tabularnewline
186 & 0 & 5.61538461538461 & -5.61538461538461 \tabularnewline
187 & 15 & 5.61538461538461 & 9.38461538461539 \tabularnewline
188 & 4 & 5.61538461538461 & -1.61538461538461 \tabularnewline
189 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
190 & 111 & 121.976744186047 & -10.9767441860465 \tabularnewline
191 & 85 & 85.2608695652174 & -0.260869565217391 \tabularnewline
192 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
193 & 40 & 40.375 & -0.375 \tabularnewline
194 & 80 & 85.2608695652174 & -5.26086956521739 \tabularnewline
195 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
196 & 48 & 40.375 & 7.625 \tabularnewline
197 & 76 & 76.0952380952381 & -0.095238095238102 \tabularnewline
198 & 51 & 49.95 & 1.05 \tabularnewline
199 & 67 & 63.0526315789474 & 3.94736842105263 \tabularnewline
200 & 59 & 58.1111111111111 & 0.888888888888886 \tabularnewline
201 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
202 & 76 & 85.2608695652174 & -9.26086956521739 \tabularnewline
203 & 60 & 58.1111111111111 & 1.88888888888889 \tabularnewline
204 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
205 & 71 & 70 & 1 \tabularnewline
206 & 76 & 76.0952380952381 & -0.095238095238102 \tabularnewline
207 & 62 & 63.0526315789474 & -1.05263157894737 \tabularnewline
208 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
209 & 67 & 70 & -3 \tabularnewline
210 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
211 & 30 & 25.75 & 4.25 \tabularnewline
212 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
213 & 68 & 70 & -2 \tabularnewline
214 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
215 & 91 & 85.2608695652174 & 5.73913043478261 \tabularnewline
216 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
217 & 52 & 49.95 & 2.05 \tabularnewline
218 & 49 & 49.95 & -0.950000000000003 \tabularnewline
219 & 62 & 63.0526315789474 & -1.05263157894737 \tabularnewline
220 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
221 & 76 & 76.0952380952381 & -0.095238095238102 \tabularnewline
222 & 88 & 85.2608695652174 & 2.73913043478261 \tabularnewline
223 & 66 & 63.0526315789474 & 2.94736842105263 \tabularnewline
224 & 71 & 70 & 1 \tabularnewline
225 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
226 & 48 & 40.375 & 7.625 \tabularnewline
227 & 25 & 25.75 & -0.75 \tabularnewline
228 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
229 & 41 & 49.95 & -8.95 \tabularnewline
230 & 90 & 85.2608695652174 & 4.73913043478261 \tabularnewline
231 & 66 & 63.0526315789474 & 2.94736842105263 \tabularnewline
232 & 54 & 49.95 & 4.05 \tabularnewline
233 & 59 & 58.1111111111111 & 0.888888888888886 \tabularnewline
234 & 60 & 63.0526315789474 & -3.05263157894737 \tabularnewline
235 & 77 & 76.0952380952381 & 0.904761904761898 \tabularnewline
236 & 68 & 70 & -2 \tabularnewline
237 & 72 & 70 & 2 \tabularnewline
238 & 67 & 63.0526315789474 & 3.94736842105263 \tabularnewline
239 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
240 & 63 & 63.0526315789474 & -0.0526315789473699 \tabularnewline
241 & 59 & 58.1111111111111 & 0.888888888888886 \tabularnewline
242 & 84 & 76.0952380952381 & 7.9047619047619 \tabularnewline
243 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
244 & 56 & 49.95 & 6.05 \tabularnewline
245 & 54 & 58.1111111111111 & -4.11111111111111 \tabularnewline
246 & 67 & 63.0526315789474 & 3.94736842105263 \tabularnewline
247 & 58 & 58.1111111111111 & -0.111111111111114 \tabularnewline
248 & 59 & 58.1111111111111 & 0.888888888888886 \tabularnewline
249 & 40 & 40.375 & -0.375 \tabularnewline
250 & 22 & 25.75 & -3.75 \tabularnewline
251 & 83 & 85.2608695652174 & -2.26086956521739 \tabularnewline
252 & 81 & 76.0952380952381 & 4.9047619047619 \tabularnewline
253 & 2 & 5.61538461538461 & -3.61538461538461 \tabularnewline
254 & 72 & 70 & 2 \tabularnewline
255 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
256 & 15 & 5.61538461538461 & 9.38461538461539 \tabularnewline
257 & 32 & 40.375 & -8.375 \tabularnewline
258 & 62 & 63.0526315789474 & -1.05263157894737 \tabularnewline
259 & 58 & 63.0526315789474 & -5.05263157894737 \tabularnewline
260 & 36 & 40.375 & -4.375 \tabularnewline
261 & 59 & 63.0526315789474 & -4.05263157894737 \tabularnewline
262 & 68 & 63.0526315789474 & 4.94736842105263 \tabularnewline
263 & 21 & 25.75 & -4.75 \tabularnewline
264 & 55 & 58.1111111111111 & -3.11111111111111 \tabularnewline
265 & 54 & 49.95 & 4.05 \tabularnewline
266 & 55 & 49.95 & 5.05 \tabularnewline
267 & 72 & 70 & 2 \tabularnewline
268 & 41 & 40.375 & 0.625 \tabularnewline
269 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
270 & 67 & 76.0952380952381 & -9.0952380952381 \tabularnewline
271 & 76 & 76.0952380952381 & -0.095238095238102 \tabularnewline
272 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
273 & 3 & 5.61538461538461 & -2.61538461538461 \tabularnewline
274 & 63 & 63.0526315789474 & -0.0526315789473699 \tabularnewline
275 & 40 & 40.375 & -0.375 \tabularnewline
276 & 69 & 76.0952380952381 & -7.0952380952381 \tabularnewline
277 & 48 & 40.375 & 7.625 \tabularnewline
278 & 8 & 5.61538461538461 & 2.38461538461539 \tabularnewline
279 & 52 & 49.95 & 2.05 \tabularnewline
280 & 66 & 63.0526315789474 & 2.94736842105263 \tabularnewline
281 & 76 & 76.0952380952381 & -0.095238095238102 \tabularnewline
282 & 43 & 49.95 & -6.95 \tabularnewline
283 & 39 & 40.375 & -1.375 \tabularnewline
284 & 14 & 5.61538461538461 & 8.38461538461539 \tabularnewline
285 & 61 & 63.0526315789474 & -2.05263157894737 \tabularnewline
286 & 71 & 76.0952380952381 & -5.0952380952381 \tabularnewline
287 & 44 & 40.375 & 3.625 \tabularnewline
288 & 60 & 58.1111111111111 & 1.88888888888889 \tabularnewline
289 & 64 & 63.0526315789474 & 0.94736842105263 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197196&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]115[/C][C]111.588235294118[/C][C]3.41176470588235[/C][/ROW]
[ROW][C]2[/C][C]109[/C][C]106.133333333333[/C][C]2.86666666666666[/C][/ROW]
[ROW][C]3[/C][C]146[/C][C]141.407407407407[/C][C]4.59259259259258[/C][/ROW]
[ROW][C]4[/C][C]116[/C][C]111.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]5[/C][C]68[/C][C]85.2608695652174[/C][C]-17.2608695652174[/C][/ROW]
[ROW][C]6[/C][C]101[/C][C]95[/C][C]6[/C][/ROW]
[ROW][C]7[/C][C]96[/C][C]95[/C][C]1[/C][/ROW]
[ROW][C]8[/C][C]67[/C][C]70[/C][C]-3[/C][/ROW]
[ROW][C]9[/C][C]44[/C][C]40.375[/C][C]3.625[/C][/ROW]
[ROW][C]10[/C][C]100[/C][C]95[/C][C]5[/C][/ROW]
[ROW][C]11[/C][C]93[/C][C]95[/C][C]-2[/C][/ROW]
[ROW][C]12[/C][C]140[/C][C]141.407407407407[/C][C]-1.40740740740742[/C][/ROW]
[ROW][C]13[/C][C]166[/C][C]165.285714285714[/C][C]0.714285714285722[/C][/ROW]
[ROW][C]14[/C][C]99[/C][C]111.588235294118[/C][C]-12.5882352941177[/C][/ROW]
[ROW][C]15[/C][C]139[/C][C]141.407407407407[/C][C]-2.40740740740742[/C][/ROW]
[ROW][C]16[/C][C]130[/C][C]121.976744186047[/C][C]8.02325581395348[/C][/ROW]
[ROW][C]17[/C][C]181[/C][C]165.285714285714[/C][C]15.7142857142857[/C][/ROW]
[ROW][C]18[/C][C]116[/C][C]111.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]19[/C][C]116[/C][C]121.976744186047[/C][C]-5.97674418604652[/C][/ROW]
[ROW][C]20[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]21[/C][C]139[/C][C]141.407407407407[/C][C]-2.40740740740742[/C][/ROW]
[ROW][C]22[/C][C]135[/C][C]141.407407407407[/C][C]-6.40740740740742[/C][/ROW]
[ROW][C]23[/C][C]108[/C][C]111.588235294118[/C][C]-3.58823529411765[/C][/ROW]
[ROW][C]24[/C][C]89[/C][C]95[/C][C]-6[/C][/ROW]
[ROW][C]25[/C][C]156[/C][C]141.407407407407[/C][C]14.5925925925926[/C][/ROW]
[ROW][C]26[/C][C]129[/C][C]121.976744186047[/C][C]7.02325581395348[/C][/ROW]
[ROW][C]27[/C][C]118[/C][C]121.976744186047[/C][C]-3.97674418604652[/C][/ROW]
[ROW][C]28[/C][C]118[/C][C]121.976744186047[/C][C]-3.97674418604652[/C][/ROW]
[ROW][C]29[/C][C]125[/C][C]121.976744186047[/C][C]3.02325581395348[/C][/ROW]
[ROW][C]30[/C][C]95[/C][C]95[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]126[/C][C]121.976744186047[/C][C]4.02325581395348[/C][/ROW]
[ROW][C]32[/C][C]135[/C][C]121.976744186047[/C][C]13.0232558139535[/C][/ROW]
[ROW][C]33[/C][C]154[/C][C]165.285714285714[/C][C]-11.2857142857143[/C][/ROW]
[ROW][C]34[/C][C]165[/C][C]165.285714285714[/C][C]-0.285714285714278[/C][/ROW]
[ROW][C]35[/C][C]113[/C][C]111.588235294118[/C][C]1.41176470588235[/C][/ROW]
[ROW][C]36[/C][C]127[/C][C]121.976744186047[/C][C]5.02325581395348[/C][/ROW]
[ROW][C]37[/C][C]52[/C][C]49.95[/C][C]2.05[/C][/ROW]
[ROW][C]38[/C][C]121[/C][C]121.976744186047[/C][C]-0.976744186046517[/C][/ROW]
[ROW][C]39[/C][C]136[/C][C]141.407407407407[/C][C]-5.40740740740742[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]5.61538461538461[/C][C]-5.61538461538461[/C][/ROW]
[ROW][C]41[/C][C]108[/C][C]106.133333333333[/C][C]1.86666666666666[/C][/ROW]
[ROW][C]42[/C][C]46[/C][C]49.95[/C][C]-3.95[/C][/ROW]
[ROW][C]43[/C][C]54[/C][C]63.0526315789474[/C][C]-9.05263157894737[/C][/ROW]
[ROW][C]44[/C][C]124[/C][C]121.976744186047[/C][C]2.02325581395348[/C][/ROW]
[ROW][C]45[/C][C]115[/C][C]111.588235294118[/C][C]3.41176470588235[/C][/ROW]
[ROW][C]46[/C][C]128[/C][C]121.976744186047[/C][C]6.02325581395348[/C][/ROW]
[ROW][C]47[/C][C]80[/C][C]76.0952380952381[/C][C]3.9047619047619[/C][/ROW]
[ROW][C]48[/C][C]97[/C][C]106.133333333333[/C][C]-9.13333333333334[/C][/ROW]
[ROW][C]49[/C][C]104[/C][C]106.133333333333[/C][C]-2.13333333333334[/C][/ROW]
[ROW][C]50[/C][C]59[/C][C]141.407407407407[/C][C]-82.4074074074074[/C][/ROW]
[ROW][C]51[/C][C]125[/C][C]121.976744186047[/C][C]3.02325581395348[/C][/ROW]
[ROW][C]52[/C][C]82[/C][C]95[/C][C]-13[/C][/ROW]
[ROW][C]53[/C][C]149[/C][C]141.407407407407[/C][C]7.59259259259258[/C][/ROW]
[ROW][C]54[/C][C]149[/C][C]141.407407407407[/C][C]7.59259259259258[/C][/ROW]
[ROW][C]55[/C][C]122[/C][C]121.976744186047[/C][C]0.0232558139534831[/C][/ROW]
[ROW][C]56[/C][C]118[/C][C]106.133333333333[/C][C]11.8666666666667[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]5.61538461538461[/C][C]6.38461538461539[/C][/ROW]
[ROW][C]58[/C][C]144[/C][C]141.407407407407[/C][C]2.59259259259258[/C][/ROW]
[ROW][C]59[/C][C]67[/C][C]70[/C][C]-3[/C][/ROW]
[ROW][C]60[/C][C]52[/C][C]49.95[/C][C]2.05[/C][/ROW]
[ROW][C]61[/C][C]108[/C][C]111.588235294118[/C][C]-3.58823529411765[/C][/ROW]
[ROW][C]62[/C][C]166[/C][C]165.285714285714[/C][C]0.714285714285722[/C][/ROW]
[ROW][C]63[/C][C]80[/C][C]76.0952380952381[/C][C]3.9047619047619[/C][/ROW]
[ROW][C]64[/C][C]60[/C][C]63.0526315789474[/C][C]-3.05263157894737[/C][/ROW]
[ROW][C]65[/C][C]107[/C][C]106.133333333333[/C][C]0.86666666666666[/C][/ROW]
[ROW][C]66[/C][C]127[/C][C]121.976744186047[/C][C]5.02325581395348[/C][/ROW]
[ROW][C]67[/C][C]107[/C][C]106.133333333333[/C][C]0.86666666666666[/C][/ROW]
[ROW][C]68[/C][C]146[/C][C]141.407407407407[/C][C]4.59259259259258[/C][/ROW]
[ROW][C]69[/C][C]84[/C][C]85.2608695652174[/C][C]-1.26086956521739[/C][/ROW]
[ROW][C]70[/C][C]141[/C][C]141.407407407407[/C][C]-0.407407407407419[/C][/ROW]
[ROW][C]71[/C][C]123[/C][C]121.976744186047[/C][C]1.02325581395348[/C][/ROW]
[ROW][C]72[/C][C]111[/C][C]111.588235294118[/C][C]-0.588235294117652[/C][/ROW]
[ROW][C]73[/C][C]98[/C][C]95[/C][C]3[/C][/ROW]
[ROW][C]74[/C][C]105[/C][C]106.133333333333[/C][C]-1.13333333333334[/C][/ROW]
[ROW][C]75[/C][C]135[/C][C]141.407407407407[/C][C]-6.40740740740742[/C][/ROW]
[ROW][C]76[/C][C]107[/C][C]106.133333333333[/C][C]0.86666666666666[/C][/ROW]
[ROW][C]77[/C][C]85[/C][C]85.2608695652174[/C][C]-0.260869565217391[/C][/ROW]
[ROW][C]78[/C][C]155[/C][C]141.407407407407[/C][C]13.5925925925926[/C][/ROW]
[ROW][C]79[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]80[/C][C]155[/C][C]141.407407407407[/C][C]13.5925925925926[/C][/ROW]
[ROW][C]81[/C][C]104[/C][C]106.133333333333[/C][C]-2.13333333333334[/C][/ROW]
[ROW][C]82[/C][C]132[/C][C]121.976744186047[/C][C]10.0232558139535[/C][/ROW]
[ROW][C]83[/C][C]127[/C][C]121.976744186047[/C][C]5.02325581395348[/C][/ROW]
[ROW][C]84[/C][C]108[/C][C]106.133333333333[/C][C]1.86666666666666[/C][/ROW]
[ROW][C]85[/C][C]129[/C][C]121.976744186047[/C][C]7.02325581395348[/C][/ROW]
[ROW][C]86[/C][C]116[/C][C]111.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]87[/C][C]122[/C][C]121.976744186047[/C][C]0.0232558139534831[/C][/ROW]
[ROW][C]88[/C][C]85[/C][C]85.2608695652174[/C][C]-0.260869565217391[/C][/ROW]
[ROW][C]89[/C][C]147[/C][C]141.407407407407[/C][C]5.59259259259258[/C][/ROW]
[ROW][C]90[/C][C]99[/C][C]95[/C][C]4[/C][/ROW]
[ROW][C]91[/C][C]87[/C][C]121.976744186047[/C][C]-34.9767441860465[/C][/ROW]
[ROW][C]92[/C][C]28[/C][C]25.75[/C][C]2.25[/C][/ROW]
[ROW][C]93[/C][C]90[/C][C]85.2608695652174[/C][C]4.73913043478261[/C][/ROW]
[ROW][C]94[/C][C]109[/C][C]111.588235294118[/C][C]-2.58823529411765[/C][/ROW]
[ROW][C]95[/C][C]78[/C][C]76.0952380952381[/C][C]1.9047619047619[/C][/ROW]
[ROW][C]96[/C][C]111[/C][C]111.588235294118[/C][C]-0.588235294117652[/C][/ROW]
[ROW][C]97[/C][C]158[/C][C]165.285714285714[/C][C]-7.28571428571428[/C][/ROW]
[ROW][C]98[/C][C]141[/C][C]141.407407407407[/C][C]-0.407407407407419[/C][/ROW]
[ROW][C]99[/C][C]122[/C][C]121.976744186047[/C][C]0.0232558139534831[/C][/ROW]
[ROW][C]100[/C][C]124[/C][C]121.976744186047[/C][C]2.02325581395348[/C][/ROW]
[ROW][C]101[/C][C]93[/C][C]95[/C][C]-2[/C][/ROW]
[ROW][C]102[/C][C]124[/C][C]121.976744186047[/C][C]2.02325581395348[/C][/ROW]
[ROW][C]103[/C][C]112[/C][C]111.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]104[/C][C]108[/C][C]106.133333333333[/C][C]1.86666666666666[/C][/ROW]
[ROW][C]105[/C][C]99[/C][C]106.133333333333[/C][C]-7.13333333333334[/C][/ROW]
[ROW][C]106[/C][C]117[/C][C]121.976744186047[/C][C]-4.97674418604652[/C][/ROW]
[ROW][C]107[/C][C]199[/C][C]165.285714285714[/C][C]33.7142857142857[/C][/ROW]
[ROW][C]108[/C][C]78[/C][C]76.0952380952381[/C][C]1.9047619047619[/C][/ROW]
[ROW][C]109[/C][C]91[/C][C]85.2608695652174[/C][C]5.73913043478261[/C][/ROW]
[ROW][C]110[/C][C]158[/C][C]165.285714285714[/C][C]-7.28571428571428[/C][/ROW]
[ROW][C]111[/C][C]126[/C][C]121.976744186047[/C][C]4.02325581395348[/C][/ROW]
[ROW][C]112[/C][C]122[/C][C]121.976744186047[/C][C]0.0232558139534831[/C][/ROW]
[ROW][C]113[/C][C]71[/C][C]76.0952380952381[/C][C]-5.0952380952381[/C][/ROW]
[ROW][C]114[/C][C]75[/C][C]76.0952380952381[/C][C]-1.0952380952381[/C][/ROW]
[ROW][C]115[/C][C]115[/C][C]121.976744186047[/C][C]-6.97674418604652[/C][/ROW]
[ROW][C]116[/C][C]119[/C][C]121.976744186047[/C][C]-2.97674418604652[/C][/ROW]
[ROW][C]117[/C][C]124[/C][C]121.976744186047[/C][C]2.02325581395348[/C][/ROW]
[ROW][C]118[/C][C]72[/C][C]70[/C][C]2[/C][/ROW]
[ROW][C]119[/C][C]91[/C][C]85.2608695652174[/C][C]5.73913043478261[/C][/ROW]
[ROW][C]120[/C][C]45[/C][C]63.0526315789474[/C][C]-18.0526315789474[/C][/ROW]
[ROW][C]121[/C][C]78[/C][C]76.0952380952381[/C][C]1.9047619047619[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]40.375[/C][C]-1.375[/C][/ROW]
[ROW][C]123[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]124[/C][C]119[/C][C]111.588235294118[/C][C]7.41176470588235[/C][/ROW]
[ROW][C]125[/C][C]117[/C][C]121.976744186047[/C][C]-4.97674418604652[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]40.375[/C][C]-1.375[/C][/ROW]
[ROW][C]127[/C][C]50[/C][C]49.95[/C][C]0.0499999999999972[/C][/ROW]
[ROW][C]128[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]129[/C][C]155[/C][C]165.285714285714[/C][C]-10.2857142857143[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]5.61538461538461[/C][C]-5.61538461538461[/C][/ROW]
[ROW][C]131[/C][C]36[/C][C]40.375[/C][C]-4.375[/C][/ROW]
[ROW][C]132[/C][C]123[/C][C]121.976744186047[/C][C]1.02325581395348[/C][/ROW]
[ROW][C]133[/C][C]32[/C][C]40.375[/C][C]-8.375[/C][/ROW]
[ROW][C]134[/C][C]99[/C][C]95[/C][C]4[/C][/ROW]
[ROW][C]135[/C][C]136[/C][C]141.407407407407[/C][C]-5.40740740740742[/C][/ROW]
[ROW][C]136[/C][C]117[/C][C]121.976744186047[/C][C]-4.97674418604652[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]5.61538461538461[/C][C]-5.61538461538461[/C][/ROW]
[ROW][C]138[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]139[/C][C]39[/C][C]49.95[/C][C]-10.95[/C][/ROW]
[ROW][C]140[/C][C]25[/C][C]25.75[/C][C]-0.75[/C][/ROW]
[ROW][C]141[/C][C]52[/C][C]49.95[/C][C]2.05[/C][/ROW]
[ROW][C]142[/C][C]75[/C][C]76.0952380952381[/C][C]-1.0952380952381[/C][/ROW]
[ROW][C]143[/C][C]71[/C][C]70[/C][C]1[/C][/ROW]
[ROW][C]144[/C][C]124[/C][C]121.976744186047[/C][C]2.02325581395348[/C][/ROW]
[ROW][C]145[/C][C]151[/C][C]141.407407407407[/C][C]9.59259259259258[/C][/ROW]
[ROW][C]146[/C][C]71[/C][C]85.2608695652174[/C][C]-14.2608695652174[/C][/ROW]
[ROW][C]147[/C][C]145[/C][C]141.407407407407[/C][C]3.59259259259258[/C][/ROW]
[ROW][C]148[/C][C]87[/C][C]85.2608695652174[/C][C]1.73913043478261[/C][/ROW]
[ROW][C]149[/C][C]27[/C][C]25.75[/C][C]1.25[/C][/ROW]
[ROW][C]150[/C][C]131[/C][C]121.976744186047[/C][C]9.02325581395348[/C][/ROW]
[ROW][C]151[/C][C]162[/C][C]165.285714285714[/C][C]-3.28571428571428[/C][/ROW]
[ROW][C]152[/C][C]165[/C][C]165.285714285714[/C][C]-0.285714285714278[/C][/ROW]
[ROW][C]153[/C][C]54[/C][C]49.95[/C][C]4.05[/C][/ROW]
[ROW][C]154[/C][C]159[/C][C]165.285714285714[/C][C]-6.28571428571428[/C][/ROW]
[ROW][C]155[/C][C]147[/C][C]141.407407407407[/C][C]5.59259259259258[/C][/ROW]
[ROW][C]156[/C][C]170[/C][C]165.285714285714[/C][C]4.71428571428572[/C][/ROW]
[ROW][C]157[/C][C]119[/C][C]121.976744186047[/C][C]-2.97674418604652[/C][/ROW]
[ROW][C]158[/C][C]49[/C][C]49.95[/C][C]-0.950000000000003[/C][/ROW]
[ROW][C]159[/C][C]104[/C][C]106.133333333333[/C][C]-2.13333333333334[/C][/ROW]
[ROW][C]160[/C][C]120[/C][C]121.976744186047[/C][C]-1.97674418604652[/C][/ROW]
[ROW][C]161[/C][C]150[/C][C]141.407407407407[/C][C]8.59259259259258[/C][/ROW]
[ROW][C]162[/C][C]112[/C][C]111.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]163[/C][C]59[/C][C]63.0526315789474[/C][C]-4.05263157894737[/C][/ROW]
[ROW][C]164[/C][C]136[/C][C]141.407407407407[/C][C]-5.40740740740742[/C][/ROW]
[ROW][C]165[/C][C]107[/C][C]111.588235294118[/C][C]-4.58823529411765[/C][/ROW]
[ROW][C]166[/C][C]130[/C][C]121.976744186047[/C][C]8.02325581395348[/C][/ROW]
[ROW][C]167[/C][C]115[/C][C]121.976744186047[/C][C]-6.97674418604652[/C][/ROW]
[ROW][C]168[/C][C]107[/C][C]106.133333333333[/C][C]0.86666666666666[/C][/ROW]
[ROW][C]169[/C][C]75[/C][C]76.0952380952381[/C][C]-1.0952380952381[/C][/ROW]
[ROW][C]170[/C][C]71[/C][C]70[/C][C]1[/C][/ROW]
[ROW][C]171[/C][C]120[/C][C]121.976744186047[/C][C]-1.97674418604652[/C][/ROW]
[ROW][C]172[/C][C]116[/C][C]121.976744186047[/C][C]-5.97674418604652[/C][/ROW]
[ROW][C]173[/C][C]79[/C][C]76.0952380952381[/C][C]2.9047619047619[/C][/ROW]
[ROW][C]174[/C][C]150[/C][C]141.407407407407[/C][C]8.59259259259258[/C][/ROW]
[ROW][C]175[/C][C]156[/C][C]165.285714285714[/C][C]-9.28571428571428[/C][/ROW]
[ROW][C]176[/C][C]51[/C][C]49.95[/C][C]1.05[/C][/ROW]
[ROW][C]177[/C][C]118[/C][C]121.976744186047[/C][C]-3.97674418604652[/C][/ROW]
[ROW][C]178[/C][C]71[/C][C]70[/C][C]1[/C][/ROW]
[ROW][C]179[/C][C]144[/C][C]141.407407407407[/C][C]2.59259259259258[/C][/ROW]
[ROW][C]180[/C][C]47[/C][C]49.95[/C][C]-2.95[/C][/ROW]
[ROW][C]181[/C][C]28[/C][C]25.75[/C][C]2.25[/C][/ROW]
[ROW][C]182[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]5.61538461538461[/C][C]-5.61538461538461[/C][/ROW]
[ROW][C]184[/C][C]110[/C][C]111.588235294118[/C][C]-1.58823529411765[/C][/ROW]
[ROW][C]185[/C][C]147[/C][C]141.407407407407[/C][C]5.59259259259258[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]5.61538461538461[/C][C]-5.61538461538461[/C][/ROW]
[ROW][C]187[/C][C]15[/C][C]5.61538461538461[/C][C]9.38461538461539[/C][/ROW]
[ROW][C]188[/C][C]4[/C][C]5.61538461538461[/C][C]-1.61538461538461[/C][/ROW]
[ROW][C]189[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]190[/C][C]111[/C][C]121.976744186047[/C][C]-10.9767441860465[/C][/ROW]
[ROW][C]191[/C][C]85[/C][C]85.2608695652174[/C][C]-0.260869565217391[/C][/ROW]
[ROW][C]192[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]193[/C][C]40[/C][C]40.375[/C][C]-0.375[/C][/ROW]
[ROW][C]194[/C][C]80[/C][C]85.2608695652174[/C][C]-5.26086956521739[/C][/ROW]
[ROW][C]195[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]196[/C][C]48[/C][C]40.375[/C][C]7.625[/C][/ROW]
[ROW][C]197[/C][C]76[/C][C]76.0952380952381[/C][C]-0.095238095238102[/C][/ROW]
[ROW][C]198[/C][C]51[/C][C]49.95[/C][C]1.05[/C][/ROW]
[ROW][C]199[/C][C]67[/C][C]63.0526315789474[/C][C]3.94736842105263[/C][/ROW]
[ROW][C]200[/C][C]59[/C][C]58.1111111111111[/C][C]0.888888888888886[/C][/ROW]
[ROW][C]201[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]202[/C][C]76[/C][C]85.2608695652174[/C][C]-9.26086956521739[/C][/ROW]
[ROW][C]203[/C][C]60[/C][C]58.1111111111111[/C][C]1.88888888888889[/C][/ROW]
[ROW][C]204[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]205[/C][C]71[/C][C]70[/C][C]1[/C][/ROW]
[ROW][C]206[/C][C]76[/C][C]76.0952380952381[/C][C]-0.095238095238102[/C][/ROW]
[ROW][C]207[/C][C]62[/C][C]63.0526315789474[/C][C]-1.05263157894737[/C][/ROW]
[ROW][C]208[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]209[/C][C]67[/C][C]70[/C][C]-3[/C][/ROW]
[ROW][C]210[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]211[/C][C]30[/C][C]25.75[/C][C]4.25[/C][/ROW]
[ROW][C]212[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]213[/C][C]68[/C][C]70[/C][C]-2[/C][/ROW]
[ROW][C]214[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]215[/C][C]91[/C][C]85.2608695652174[/C][C]5.73913043478261[/C][/ROW]
[ROW][C]216[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]217[/C][C]52[/C][C]49.95[/C][C]2.05[/C][/ROW]
[ROW][C]218[/C][C]49[/C][C]49.95[/C][C]-0.950000000000003[/C][/ROW]
[ROW][C]219[/C][C]62[/C][C]63.0526315789474[/C][C]-1.05263157894737[/C][/ROW]
[ROW][C]220[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]221[/C][C]76[/C][C]76.0952380952381[/C][C]-0.095238095238102[/C][/ROW]
[ROW][C]222[/C][C]88[/C][C]85.2608695652174[/C][C]2.73913043478261[/C][/ROW]
[ROW][C]223[/C][C]66[/C][C]63.0526315789474[/C][C]2.94736842105263[/C][/ROW]
[ROW][C]224[/C][C]71[/C][C]70[/C][C]1[/C][/ROW]
[ROW][C]225[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]226[/C][C]48[/C][C]40.375[/C][C]7.625[/C][/ROW]
[ROW][C]227[/C][C]25[/C][C]25.75[/C][C]-0.75[/C][/ROW]
[ROW][C]228[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]229[/C][C]41[/C][C]49.95[/C][C]-8.95[/C][/ROW]
[ROW][C]230[/C][C]90[/C][C]85.2608695652174[/C][C]4.73913043478261[/C][/ROW]
[ROW][C]231[/C][C]66[/C][C]63.0526315789474[/C][C]2.94736842105263[/C][/ROW]
[ROW][C]232[/C][C]54[/C][C]49.95[/C][C]4.05[/C][/ROW]
[ROW][C]233[/C][C]59[/C][C]58.1111111111111[/C][C]0.888888888888886[/C][/ROW]
[ROW][C]234[/C][C]60[/C][C]63.0526315789474[/C][C]-3.05263157894737[/C][/ROW]
[ROW][C]235[/C][C]77[/C][C]76.0952380952381[/C][C]0.904761904761898[/C][/ROW]
[ROW][C]236[/C][C]68[/C][C]70[/C][C]-2[/C][/ROW]
[ROW][C]237[/C][C]72[/C][C]70[/C][C]2[/C][/ROW]
[ROW][C]238[/C][C]67[/C][C]63.0526315789474[/C][C]3.94736842105263[/C][/ROW]
[ROW][C]239[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]240[/C][C]63[/C][C]63.0526315789474[/C][C]-0.0526315789473699[/C][/ROW]
[ROW][C]241[/C][C]59[/C][C]58.1111111111111[/C][C]0.888888888888886[/C][/ROW]
[ROW][C]242[/C][C]84[/C][C]76.0952380952381[/C][C]7.9047619047619[/C][/ROW]
[ROW][C]243[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]244[/C][C]56[/C][C]49.95[/C][C]6.05[/C][/ROW]
[ROW][C]245[/C][C]54[/C][C]58.1111111111111[/C][C]-4.11111111111111[/C][/ROW]
[ROW][C]246[/C][C]67[/C][C]63.0526315789474[/C][C]3.94736842105263[/C][/ROW]
[ROW][C]247[/C][C]58[/C][C]58.1111111111111[/C][C]-0.111111111111114[/C][/ROW]
[ROW][C]248[/C][C]59[/C][C]58.1111111111111[/C][C]0.888888888888886[/C][/ROW]
[ROW][C]249[/C][C]40[/C][C]40.375[/C][C]-0.375[/C][/ROW]
[ROW][C]250[/C][C]22[/C][C]25.75[/C][C]-3.75[/C][/ROW]
[ROW][C]251[/C][C]83[/C][C]85.2608695652174[/C][C]-2.26086956521739[/C][/ROW]
[ROW][C]252[/C][C]81[/C][C]76.0952380952381[/C][C]4.9047619047619[/C][/ROW]
[ROW][C]253[/C][C]2[/C][C]5.61538461538461[/C][C]-3.61538461538461[/C][/ROW]
[ROW][C]254[/C][C]72[/C][C]70[/C][C]2[/C][/ROW]
[ROW][C]255[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]5.61538461538461[/C][C]9.38461538461539[/C][/ROW]
[ROW][C]257[/C][C]32[/C][C]40.375[/C][C]-8.375[/C][/ROW]
[ROW][C]258[/C][C]62[/C][C]63.0526315789474[/C][C]-1.05263157894737[/C][/ROW]
[ROW][C]259[/C][C]58[/C][C]63.0526315789474[/C][C]-5.05263157894737[/C][/ROW]
[ROW][C]260[/C][C]36[/C][C]40.375[/C][C]-4.375[/C][/ROW]
[ROW][C]261[/C][C]59[/C][C]63.0526315789474[/C][C]-4.05263157894737[/C][/ROW]
[ROW][C]262[/C][C]68[/C][C]63.0526315789474[/C][C]4.94736842105263[/C][/ROW]
[ROW][C]263[/C][C]21[/C][C]25.75[/C][C]-4.75[/C][/ROW]
[ROW][C]264[/C][C]55[/C][C]58.1111111111111[/C][C]-3.11111111111111[/C][/ROW]
[ROW][C]265[/C][C]54[/C][C]49.95[/C][C]4.05[/C][/ROW]
[ROW][C]266[/C][C]55[/C][C]49.95[/C][C]5.05[/C][/ROW]
[ROW][C]267[/C][C]72[/C][C]70[/C][C]2[/C][/ROW]
[ROW][C]268[/C][C]41[/C][C]40.375[/C][C]0.625[/C][/ROW]
[ROW][C]269[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]270[/C][C]67[/C][C]76.0952380952381[/C][C]-9.0952380952381[/C][/ROW]
[ROW][C]271[/C][C]76[/C][C]76.0952380952381[/C][C]-0.095238095238102[/C][/ROW]
[ROW][C]272[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[ROW][C]273[/C][C]3[/C][C]5.61538461538461[/C][C]-2.61538461538461[/C][/ROW]
[ROW][C]274[/C][C]63[/C][C]63.0526315789474[/C][C]-0.0526315789473699[/C][/ROW]
[ROW][C]275[/C][C]40[/C][C]40.375[/C][C]-0.375[/C][/ROW]
[ROW][C]276[/C][C]69[/C][C]76.0952380952381[/C][C]-7.0952380952381[/C][/ROW]
[ROW][C]277[/C][C]48[/C][C]40.375[/C][C]7.625[/C][/ROW]
[ROW][C]278[/C][C]8[/C][C]5.61538461538461[/C][C]2.38461538461539[/C][/ROW]
[ROW][C]279[/C][C]52[/C][C]49.95[/C][C]2.05[/C][/ROW]
[ROW][C]280[/C][C]66[/C][C]63.0526315789474[/C][C]2.94736842105263[/C][/ROW]
[ROW][C]281[/C][C]76[/C][C]76.0952380952381[/C][C]-0.095238095238102[/C][/ROW]
[ROW][C]282[/C][C]43[/C][C]49.95[/C][C]-6.95[/C][/ROW]
[ROW][C]283[/C][C]39[/C][C]40.375[/C][C]-1.375[/C][/ROW]
[ROW][C]284[/C][C]14[/C][C]5.61538461538461[/C][C]8.38461538461539[/C][/ROW]
[ROW][C]285[/C][C]61[/C][C]63.0526315789474[/C][C]-2.05263157894737[/C][/ROW]
[ROW][C]286[/C][C]71[/C][C]76.0952380952381[/C][C]-5.0952380952381[/C][/ROW]
[ROW][C]287[/C][C]44[/C][C]40.375[/C][C]3.625[/C][/ROW]
[ROW][C]288[/C][C]60[/C][C]58.1111111111111[/C][C]1.88888888888889[/C][/ROW]
[ROW][C]289[/C][C]64[/C][C]63.0526315789474[/C][C]0.94736842105263[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197196&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197196&T=2

As an alternative you can also use a QR Code:  

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

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
1115111.5882352941183.41176470588235
2109106.1333333333332.86666666666666
3146141.4074074074074.59259259259258
4116111.5882352941184.41176470588235
56885.2608695652174-17.2608695652174
6101956
796951
86770-3
94440.3753.625
10100955
119395-2
12140141.407407407407-1.40740740740742
13166165.2857142857140.714285714285722
1499111.588235294118-12.5882352941177
15139141.407407407407-2.40740740740742
16130121.9767441860478.02325581395348
17181165.28571428571415.7142857142857
18116111.5882352941184.41176470588235
19116121.976744186047-5.97674418604652
208885.26086956521742.73913043478261
21139141.407407407407-2.40740740740742
22135141.407407407407-6.40740740740742
23108111.588235294118-3.58823529411765
248995-6
25156141.40740740740714.5925925925926
26129121.9767441860477.02325581395348
27118121.976744186047-3.97674418604652
28118121.976744186047-3.97674418604652
29125121.9767441860473.02325581395348
3095950
31126121.9767441860474.02325581395348
32135121.97674418604713.0232558139535
33154165.285714285714-11.2857142857143
34165165.285714285714-0.285714285714278
35113111.5882352941181.41176470588235
36127121.9767441860475.02325581395348
375249.952.05
38121121.976744186047-0.976744186046517
39136141.407407407407-5.40740740740742
4005.61538461538461-5.61538461538461
41108106.1333333333331.86666666666666
424649.95-3.95
435463.0526315789474-9.05263157894737
44124121.9767441860472.02325581395348
45115111.5882352941183.41176470588235
46128121.9767441860476.02325581395348
478076.09523809523813.9047619047619
4897106.133333333333-9.13333333333334
49104106.133333333333-2.13333333333334
5059141.407407407407-82.4074074074074
51125121.9767441860473.02325581395348
528295-13
53149141.4074074074077.59259259259258
54149141.4074074074077.59259259259258
55122121.9767441860470.0232558139534831
56118106.13333333333311.8666666666667
57125.615384615384616.38461538461539
58144141.4074074074072.59259259259258
596770-3
605249.952.05
61108111.588235294118-3.58823529411765
62166165.2857142857140.714285714285722
638076.09523809523813.9047619047619
646063.0526315789474-3.05263157894737
65107106.1333333333330.86666666666666
66127121.9767441860475.02325581395348
67107106.1333333333330.86666666666666
68146141.4074074074074.59259259259258
698485.2608695652174-1.26086956521739
70141141.407407407407-0.407407407407419
71123121.9767441860471.02325581395348
72111111.588235294118-0.588235294117652
7398953
74105106.133333333333-1.13333333333334
75135141.407407407407-6.40740740740742
76107106.1333333333330.86666666666666
778585.2608695652174-0.260869565217391
78155141.40740740740713.5925925925926
798885.26086956521742.73913043478261
80155141.40740740740713.5925925925926
81104106.133333333333-2.13333333333334
82132121.97674418604710.0232558139535
83127121.9767441860475.02325581395348
84108106.1333333333331.86666666666666
85129121.9767441860477.02325581395348
86116111.5882352941184.41176470588235
87122121.9767441860470.0232558139534831
888585.2608695652174-0.260869565217391
89147141.4074074074075.59259259259258
9099954
9187121.976744186047-34.9767441860465
922825.752.25
939085.26086956521744.73913043478261
94109111.588235294118-2.58823529411765
957876.09523809523811.9047619047619
96111111.588235294118-0.588235294117652
97158165.285714285714-7.28571428571428
98141141.407407407407-0.407407407407419
99122121.9767441860470.0232558139534831
100124121.9767441860472.02325581395348
1019395-2
102124121.9767441860472.02325581395348
103112111.5882352941180.411764705882348
104108106.1333333333331.86666666666666
10599106.133333333333-7.13333333333334
106117121.976744186047-4.97674418604652
107199165.28571428571433.7142857142857
1087876.09523809523811.9047619047619
1099185.26086956521745.73913043478261
110158165.285714285714-7.28571428571428
111126121.9767441860474.02325581395348
112122121.9767441860470.0232558139534831
1137176.0952380952381-5.0952380952381
1147576.0952380952381-1.0952380952381
115115121.976744186047-6.97674418604652
116119121.976744186047-2.97674418604652
117124121.9767441860472.02325581395348
11872702
1199185.26086956521745.73913043478261
1204563.0526315789474-18.0526315789474
1217876.09523809523811.9047619047619
1223940.375-1.375
1236863.05263157894744.94736842105263
124119111.5882352941187.41176470588235
125117121.976744186047-4.97674418604652
1263940.375-1.375
1275049.950.0499999999999972
1288885.26086956521742.73913043478261
129155165.285714285714-10.2857142857143
13005.61538461538461-5.61538461538461
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Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 7 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}