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R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Wed, 21 Dec 2011 15:44:11 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/21/t1324500282nitqb1es4i8owvj.htm/, Retrieved Tue, 07 May 2024 04:37:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159001, Retrieved Tue, 07 May 2024 04:37:12 +0000

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Estimated Impact

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)] [Regression Trees] [2011-12-08 20:43:52] [bc54fcbdb4f9c071218969745a8ec94b]
-   PD    [Recursive Partitioning (Regression Trees)] [] [2011-12-21 20:38:21] [bdca8f3e7c3554be8c1291e54f61d441]
-    D        [Recursive Partitioning (Regression Trees)] [] [2011-12-21 20:44:11] [fe5ec8748c528a1557751a5a0f6a19ab] [Current]
-               [Recursive Partitioning (Regression Trees)] [] [2011-12-21 22:11:01] [bdca8f3e7c3554be8c1291e54f61d441] 
-    D            [Recursive Partitioning (Regression Trees)] [] [2011-12-21 22:14:27] [bdca8f3e7c3554be8c1291e54f61d441] 
-    D              [Recursive Partitioning (Regression Trees)] [] [2011-12-21 23:43:30] [bdca8f3e7c3554be8c1291e54f61d441] 

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Dataseries X:

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Histogram

Boxplots

278691	71	494	96	42	159	140824
197623	70	477	75	38	149	110459
233139	78	701	70	46	178	105079
221690	106	1150	134	42	164	112098
177540	53	395	69	30	100	43929
70849	28	179	8	35	129	76173
566234	130	2446	169	40	156	187326
33186	19	111	1	18	67	22807
226511	62	756	87	38	148	144408
245577	46	638	92	37	132	66485
317443	114	831	96	46	169	79089
248379	124	706	119	60	230	81625
200620	79	749	57	37	122	68788
367785	82	1184	139	55	191	103297
266325	87	717	87	44	162	69446
394271	183	1744	176	63	237	114948
335567	76	845	114	40	156	167949
407650	168	1360	119	43	157	125081
182016	57	514	103	32	123	125818
267365	88	692	135	52	203	136588
279428	72	847	123	49	187	112431
484574	105	1369	89	41	152	103037
196721	43	494	74	25	89	82317
197899	56	628	103	57	227	118906
256290	131	1364	158	45	165	83515
255126	132	1067	113	42	162	104581
281816	131	1112	100	45	174	103129
278027	89	636	117	43	154	83243
173134	55	610	59	36	129	37110
383613	77	1205	142	45	174	113344
302413	84	1021	136	50	195	139165
251255	81	724	50	50	186	86652
355456	96	868	141	51	197	112302
109546	45	374	46	42	157	69652
427915	103	1290	141	44	168	119442
273950	56	1186	83	42	159	69867
427825	124	1344	112	44	161	101629
247287	88	673	79	40	153	70168
115658	33	284	33	17	55	31081
386534	205	1299	149	43	166	103925
340132	83	1546	126	41	151	92622
194127	71	715	80	41	148	79011
213258	79	676	84	40	129	93487
182398	65	487	68	49	181	64520
157164	84	1051	50	52	93	93473
457592	153	2084	101	42	150	114360
78800	42	330	20	26	82	33032
213831	81	683	101	59	229	96125
368086	122	1410	150	50	193	151911
203104	62	1004	115	50	176	89256
244371	77	688	98	47	179	95676
24188	24	218	8	4	12	5950
399093	331	862	88	51	181	149695
65029	17	255	21	18	67	32551
101097	64	454	30	14	52	31701
297973	61	1185	97	41	148	100087
352671	88	728	149	61	230	169707
367083	203	1207	132	40	148	150491
371178	148	1089	161	44	160	120192
269973	88	884	89	40	155	95893
389761	149	1332	160	51	198	151715
315924	121	1190	139	29	104	176225
285807	121	1233	104	43	169	59900
282351	90	987	99	42	163	104767
250558	73	619	56	41	151	114799
265696	71	528	163	30	116	72128
215915	138	651	93	39	153	143592
247349	154	862	85	51	195	89626
260919	86	913	150	40	149	131072
182308	71	635	143	29	106	126817
256761	72	898	107	47	179	81351
73566	32	385	22	23	88	22618
263796	89	767	85	48	185	88977
207899	56	818	85	38	133	92059
228779	67	779	131	42	164	81897
363571	89	997	140	46	169	108146
382785	98	1233	152	40	153	126372
220401	109	586	81	45	166	249771
225097	67	751	136	42	164	71154
215445	68	734	102	41	146	71571
188786	49	711	69	37	141	55918
481148	130	1268	161	47	183	160141
145943	70	653	30	26	99	38692
292287	108	700	120	48	134	102812
80953	25	437	49	8	28	56622
164260	57	863	62	27	101	15986
179344	61	459	76	38	139	123534
413462	220	1580	85	41	159	108535
358697	125	1024	146	61	222	93879
180679	106	1051	165	45	171	144551
298696	102	843	89	41	154	56750
288706	82	725	167	42	154	127654
197956	66	621	48	35	129	65594
282361	77	1128	149	36	140	59938
329202	88	969	75	40	156	146975
221875	44	669	100	40	156	165904
277071	63	674	114	38	138	169265
305984	87	820	165	43	153	183500
416032	161	1366	155	65	251	165986
412530	116	1493	165	33	126	184923
297080	141	893	121	51	198	140358
318235	68	900	156	45	168	149959
200486	194	704	79	36	138	57224
43287	14	214	13	19	71	43750
189520	84	733	89	25	90	48029
255152	153	855	110	44	167	104978
288617	56	1251	129	45	172	100046
314167	93	1069	169	44	162	101047
170268	86	426	28	35	129	197426
164399	99	954	118	46	179	160902
350667	76	674	82	44	163	147172
303273	90	696	148	45	164	109432
23623	11	156	12	1	NA	1168
195849	74	779	146	40	155	83248
61857	25	192	23	11	32	25162
184709	52	546	83	51	189	45724
428191	121	1213	163	38	140	110529
21054	16	146	4	NA	NA	855
252805	52	866	81	30	111	101382
31961	22	200	18	8	25	14116
351541	122	1336	118	43	159	89506
246359	71	726	76	48	183	135356
187003	95	522	55	49	184	116066
172442	56	714	57	32	119	144244
38214	34	276	16	8	27	8773
241539	48	789	88	43	163	102153
358276	83	1031	137	52	198	117440
209821	64	502	50	53	205	104128
441447	86	1678	147	49	191	134238
348017	99	884	163	48	187	134047
439634	131	1200	142	56	210	279488
208962	40	547	77	45	166	79756
105332	44	422	42	40	145	66089
311111	355	995	94	48	187	102070
460033	192	1554	126	50	186	146760
159057	58	563	63	43	164	154771
411980	136	1811	127	46	172	165933
173486	80	749	59	40	147	64593
284582	51	648	117	45	167	92280
283913	100	905	110	46	158	67150
234203	120	659	44	37	144	128692
386740	123	1611	95	45	169	124089
246963	92	811	128	39	145	125386
173260	63	716	41	21	79	37238
346730	107	1034	146	50	194	140015
176654	58	732	147	55	212	150047
259048	90	1033	119	40	148	154451
312540	111	850	185	48	171	156349
1	        NA	NA	NA	NA	NA	NA
14688	10	85	4	NA	NA	6023
98	        1	NA	NA	NA	NA	NA
455	        2	NA	NA	NA	NA	NA
NA	        NA	NA	NA	NA	NA	NA
NA	        NA	NA	NA	NA	NA	NA
283222	91	806	85	46	141	84601
409280	163	1128	157	52	204	68946
NA	        NA	NA	NA	NA	NA	NA
203	        4	NA	NA	NA	NA	NA
7199         5	74	7	NA	NA	1644
46660	20	259	12	5	15	6179
17547	5	69	NA	1	4	3926
121550	46	309	37	48	172	52789
969	        2	NA	NA	NA	NA	NA
242228	73	687	62	34	125	100350

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159001&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159001&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159001&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.wessa.net

Goodness of Fit
Correlation	0.878
R-squared	0.7708
RMSE	57122.9524

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.878 \tabularnewline
R-squared & 0.7708 \tabularnewline
RMSE & 57122.9524 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159001&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.878[/C][/ROW]
[ROW][C]R-squared[/C][C]0.7708[/C][/ROW]
[ROW][C]RMSE[/C][C]57122.9524[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159001&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159001&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
Correlation	0.878
R-squared	0.7708
RMSE	57122.9524

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	278691	245243.1875	33447.8125
2	197623	205667.666666667	-8044.66666666666
3	233139	205667.666666667	27471.3333333333
4	221690	291580.9	-69890.9
5	177540	123447.571428571	54092.4285714286
6	70849	45265.8235294118	25583.1764705882
7	566234	441469.875	124764.125
8	33186	45265.8235294118	-12079.8235294118
9	226511	245243.1875	-18732.1875
10	245577	101530.857142857	144046.142857143
11	317443	291580.9	25862.1
12	248379	245243.1875	3135.8125
13	200620	205667.666666667	-5047.66666666666
14	367785	291580.9	76204.1
15	266325	245243.1875	21081.8125
16	394271	441469.875	-47198.875
17	335567	291580.9	43986.1
18	407650	386287.4	21362.6
19	182016	245243.1875	-63227.1875
20	267365	245243.1875	22121.8125
21	279428	291580.9	-12152.9
22	484574	386287.4	98286.6
23	196721	205667.666666667	-8946.66666666666
24	197899	245243.1875	-47344.1875
25	256290	386287.4	-129997.4
26	255126	291580.9	-36454.9
27	281816	291580.9	-9764.90000000002
28	278027	245243.1875	32783.8125
29	173134	205667.666666667	-32533.6666666667
30	383613	386287.4	-2674.40000000002
31	302413	291580.9	10832.1
32	251255	205667.666666667	45587.3333333333
33	355456	291580.9	63875.1
34	109546	123447.571428571	-13901.5714285714
35	427915	386287.4	41627.6
36	273950	291580.9	-17630.9
37	427825	386287.4	41537.6
38	247287	205667.666666667	41619.3333333333
39	115658	45265.8235294118	70392.1764705882
40	386534	386287.4	246.599999999977
41	340132	386287.4	-46155.4
42	194127	205667.666666667	-11540.6666666667
43	213258	245243.1875	-31985.1875
44	182398	205667.666666667	-23269.6666666667
45	157164	205667.666666667	-48503.6666666667
46	457592	441469.875	16122.125
47	78800	123447.571428571	-44647.5714285714
48	213831	245243.1875	-31412.1875
49	368086	386287.4	-18201.4
50	203104	291580.9	-88476.9
51	244371	245243.1875	-872.1875
52	24188	45265.8235294118	-21077.8235294118
53	399093	291580.9	107512.1
54	65029	45265.8235294118	19763.1764705882
55	101097	123447.571428571	-22350.5714285714
56	297973	291580.9	6392.09999999998
57	352671	245243.1875	107427.8125
58	367083	386287.4	-19204.4
59	371178	291580.9	79597.1
60	269973	291580.9	-21607.9
61	389761	386287.4	3473.59999999998
62	315924	291580.9	24343.1
63	285807	386287.4	-100480.4
64	282351	291580.9	-9229.90000000002
65	250558	205667.666666667	44890.3333333333
66	265696	245243.1875	20452.8125
67	215915	245243.1875	-29328.1875
68	247349	291580.9	-44231.9
69	260919	291580.9	-30661.9
70	182308	245243.1875	-62935.1875
71	256761	291580.9	-34819.9
72	73566	45265.8235294118	28300.1764705882
73	263796	245243.1875	18552.8125
74	207899	245243.1875	-37344.1875
75	228779	245243.1875	-16464.1875
76	363571	291580.9	71990.1
77	382785	386287.4	-3502.40000000002
78	220401	205667.666666667	14733.3333333333
79	225097	245243.1875	-20146.1875
80	215445	245243.1875	-29798.1875
81	188786	205667.666666667	-16881.6666666667
82	481148	386287.4	94860.6
83	145943	205667.666666667	-59724.6666666667
84	292287	245243.1875	47043.8125
85	80953	45265.8235294118	35687.1764705882
86	164260	205667.666666667	-41407.6666666667
87	179344	205667.666666667	-26323.6666666667
88	413462	441469.875	-28007.875
89	358697	291580.9	67116.1
90	180679	291580.9	-110901.9
91	298696	291580.9	7115.09999999998
92	288706	245243.1875	43462.8125
93	197956	205667.666666667	-7711.66666666666
94	282361	291580.9	-9219.90000000002
95	329202	205667.666666667	123534.333333333
96	221875	101530.857142857	120344.142857143
97	277071	245243.1875	31827.8125
98	305984	291580.9	14403.1
99	416032	386287.4	29744.6
100	412530	386287.4	26242.6
101	297080	291580.9	5499.09999999998
102	318235	291580.9	26654.1
103	200486	205667.666666667	-5181.66666666666
104	43287	45265.8235294118	-1978.82352941176
105	189520	245243.1875	-55723.1875
106	255152	291580.9	-36428.9
107	288617	386287.4	-97670.4
108	314167	291580.9	22586.1
109	170268	123447.571428571	46820.4285714286
110	164399	291580.9	-127181.9
111	350667	245243.1875	105423.8125
112	303273	245243.1875	58029.8125
113	23623	45265.8235294118	-21642.8235294118
114	195849	245243.1875	-49394.1875
115	61857	45265.8235294118	16591.1764705882
116	184709	245243.1875	-60534.1875
117	428191	386287.4	41903.6
118	21054	45265.8235294118	-24211.8235294118
119	252805	205667.666666667	47137.3333333333
120	31961	45265.8235294118	-13304.8235294118
121	351541	386287.4	-34746.4
122	246359	205667.666666667	40691.3333333333
123	187003	205667.666666667	-18664.6666666667
124	172442	205667.666666667	-33225.6666666667
125	38214	45265.8235294118	-7051.82352941176
126	241539	101530.857142857	140008.142857143
127	358276	291580.9	66695.1
128	209821	205667.666666667	4153.33333333334
129	441447	441469.875	-22.875
130	348017	291580.9	56436.1
131	439634	386287.4	53346.6
132	208962	205667.666666667	3294.33333333334
133	105332	123447.571428571	-18115.5714285714
134	311111	291580.9	19530.1
135	460033	441469.875	18563.125
136	159057	205667.666666667	-46610.6666666667
137	411980	441469.875	-29489.875
138	173486	205667.666666667	-32181.6666666667
139	284582	245243.1875	39338.8125
140	283913	291580.9	-7667.90000000002
141	234203	205667.666666667	28535.3333333333
142	386740	441469.875	-54729.875
143	246963	245243.1875	1719.8125
144	173260	205667.666666667	-32407.6666666667
145	346730	291580.9	55149.1
146	176654	245243.1875	-68589.1875
147	259048	291580.9	-32532.9
148	312540	291580.9	20959.1
149	1	291580.9	-291579.9
150	14688	45265.8235294118	-30577.8235294118
151	98	101530.857142857	-101432.857142857
152	455	101530.857142857	-101075.857142857
153	283222	245243.1875	37978.8125
154	409280	291580.9	117699.1
155	203	101530.857142857	-101327.857142857
156	7199	45265.8235294118	-38066.8235294118
157	46660	45265.8235294118	1394.17647058824
158	17547	45265.8235294118	-27718.8235294118
159	121550	123447.571428571	-1897.57142857143
160	969	101530.857142857	-100561.857142857
161	242228	205667.666666667	36560.3333333333

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 278691 & 245243.1875 & 33447.8125 \tabularnewline
2 & 197623 & 205667.666666667 & -8044.66666666666 \tabularnewline
3 & 233139 & 205667.666666667 & 27471.3333333333 \tabularnewline
4 & 221690 & 291580.9 & -69890.9 \tabularnewline
5 & 177540 & 123447.571428571 & 54092.4285714286 \tabularnewline
6 & 70849 & 45265.8235294118 & 25583.1764705882 \tabularnewline
7 & 566234 & 441469.875 & 124764.125 \tabularnewline
8 & 33186 & 45265.8235294118 & -12079.8235294118 \tabularnewline
9 & 226511 & 245243.1875 & -18732.1875 \tabularnewline
10 & 245577 & 101530.857142857 & 144046.142857143 \tabularnewline
11 & 317443 & 291580.9 & 25862.1 \tabularnewline
12 & 248379 & 245243.1875 & 3135.8125 \tabularnewline
13 & 200620 & 205667.666666667 & -5047.66666666666 \tabularnewline
14 & 367785 & 291580.9 & 76204.1 \tabularnewline
15 & 266325 & 245243.1875 & 21081.8125 \tabularnewline
16 & 394271 & 441469.875 & -47198.875 \tabularnewline
17 & 335567 & 291580.9 & 43986.1 \tabularnewline
18 & 407650 & 386287.4 & 21362.6 \tabularnewline
19 & 182016 & 245243.1875 & -63227.1875 \tabularnewline
20 & 267365 & 245243.1875 & 22121.8125 \tabularnewline
21 & 279428 & 291580.9 & -12152.9 \tabularnewline
22 & 484574 & 386287.4 & 98286.6 \tabularnewline
23 & 196721 & 205667.666666667 & -8946.66666666666 \tabularnewline
24 & 197899 & 245243.1875 & -47344.1875 \tabularnewline
25 & 256290 & 386287.4 & -129997.4 \tabularnewline
26 & 255126 & 291580.9 & -36454.9 \tabularnewline
27 & 281816 & 291580.9 & -9764.90000000002 \tabularnewline
28 & 278027 & 245243.1875 & 32783.8125 \tabularnewline
29 & 173134 & 205667.666666667 & -32533.6666666667 \tabularnewline
30 & 383613 & 386287.4 & -2674.40000000002 \tabularnewline
31 & 302413 & 291580.9 & 10832.1 \tabularnewline
32 & 251255 & 205667.666666667 & 45587.3333333333 \tabularnewline
33 & 355456 & 291580.9 & 63875.1 \tabularnewline
34 & 109546 & 123447.571428571 & -13901.5714285714 \tabularnewline
35 & 427915 & 386287.4 & 41627.6 \tabularnewline
36 & 273950 & 291580.9 & -17630.9 \tabularnewline
37 & 427825 & 386287.4 & 41537.6 \tabularnewline
38 & 247287 & 205667.666666667 & 41619.3333333333 \tabularnewline
39 & 115658 & 45265.8235294118 & 70392.1764705882 \tabularnewline
40 & 386534 & 386287.4 & 246.599999999977 \tabularnewline
41 & 340132 & 386287.4 & -46155.4 \tabularnewline
42 & 194127 & 205667.666666667 & -11540.6666666667 \tabularnewline
43 & 213258 & 245243.1875 & -31985.1875 \tabularnewline
44 & 182398 & 205667.666666667 & -23269.6666666667 \tabularnewline
45 & 157164 & 205667.666666667 & -48503.6666666667 \tabularnewline
46 & 457592 & 441469.875 & 16122.125 \tabularnewline
47 & 78800 & 123447.571428571 & -44647.5714285714 \tabularnewline
48 & 213831 & 245243.1875 & -31412.1875 \tabularnewline
49 & 368086 & 386287.4 & -18201.4 \tabularnewline
50 & 203104 & 291580.9 & -88476.9 \tabularnewline
51 & 244371 & 245243.1875 & -872.1875 \tabularnewline
52 & 24188 & 45265.8235294118 & -21077.8235294118 \tabularnewline
53 & 399093 & 291580.9 & 107512.1 \tabularnewline
54 & 65029 & 45265.8235294118 & 19763.1764705882 \tabularnewline
55 & 101097 & 123447.571428571 & -22350.5714285714 \tabularnewline
56 & 297973 & 291580.9 & 6392.09999999998 \tabularnewline
57 & 352671 & 245243.1875 & 107427.8125 \tabularnewline
58 & 367083 & 386287.4 & -19204.4 \tabularnewline
59 & 371178 & 291580.9 & 79597.1 \tabularnewline
60 & 269973 & 291580.9 & -21607.9 \tabularnewline
61 & 389761 & 386287.4 & 3473.59999999998 \tabularnewline
62 & 315924 & 291580.9 & 24343.1 \tabularnewline
63 & 285807 & 386287.4 & -100480.4 \tabularnewline
64 & 282351 & 291580.9 & -9229.90000000002 \tabularnewline
65 & 250558 & 205667.666666667 & 44890.3333333333 \tabularnewline
66 & 265696 & 245243.1875 & 20452.8125 \tabularnewline
67 & 215915 & 245243.1875 & -29328.1875 \tabularnewline
68 & 247349 & 291580.9 & -44231.9 \tabularnewline
69 & 260919 & 291580.9 & -30661.9 \tabularnewline
70 & 182308 & 245243.1875 & -62935.1875 \tabularnewline
71 & 256761 & 291580.9 & -34819.9 \tabularnewline
72 & 73566 & 45265.8235294118 & 28300.1764705882 \tabularnewline
73 & 263796 & 245243.1875 & 18552.8125 \tabularnewline
74 & 207899 & 245243.1875 & -37344.1875 \tabularnewline
75 & 228779 & 245243.1875 & -16464.1875 \tabularnewline
76 & 363571 & 291580.9 & 71990.1 \tabularnewline
77 & 382785 & 386287.4 & -3502.40000000002 \tabularnewline
78 & 220401 & 205667.666666667 & 14733.3333333333 \tabularnewline
79 & 225097 & 245243.1875 & -20146.1875 \tabularnewline
80 & 215445 & 245243.1875 & -29798.1875 \tabularnewline
81 & 188786 & 205667.666666667 & -16881.6666666667 \tabularnewline
82 & 481148 & 386287.4 & 94860.6 \tabularnewline
83 & 145943 & 205667.666666667 & -59724.6666666667 \tabularnewline
84 & 292287 & 245243.1875 & 47043.8125 \tabularnewline
85 & 80953 & 45265.8235294118 & 35687.1764705882 \tabularnewline
86 & 164260 & 205667.666666667 & -41407.6666666667 \tabularnewline
87 & 179344 & 205667.666666667 & -26323.6666666667 \tabularnewline
88 & 413462 & 441469.875 & -28007.875 \tabularnewline
89 & 358697 & 291580.9 & 67116.1 \tabularnewline
90 & 180679 & 291580.9 & -110901.9 \tabularnewline
91 & 298696 & 291580.9 & 7115.09999999998 \tabularnewline
92 & 288706 & 245243.1875 & 43462.8125 \tabularnewline
93 & 197956 & 205667.666666667 & -7711.66666666666 \tabularnewline
94 & 282361 & 291580.9 & -9219.90000000002 \tabularnewline
95 & 329202 & 205667.666666667 & 123534.333333333 \tabularnewline
96 & 221875 & 101530.857142857 & 120344.142857143 \tabularnewline
97 & 277071 & 245243.1875 & 31827.8125 \tabularnewline
98 & 305984 & 291580.9 & 14403.1 \tabularnewline
99 & 416032 & 386287.4 & 29744.6 \tabularnewline
100 & 412530 & 386287.4 & 26242.6 \tabularnewline
101 & 297080 & 291580.9 & 5499.09999999998 \tabularnewline
102 & 318235 & 291580.9 & 26654.1 \tabularnewline
103 & 200486 & 205667.666666667 & -5181.66666666666 \tabularnewline
104 & 43287 & 45265.8235294118 & -1978.82352941176 \tabularnewline
105 & 189520 & 245243.1875 & -55723.1875 \tabularnewline
106 & 255152 & 291580.9 & -36428.9 \tabularnewline
107 & 288617 & 386287.4 & -97670.4 \tabularnewline
108 & 314167 & 291580.9 & 22586.1 \tabularnewline
109 & 170268 & 123447.571428571 & 46820.4285714286 \tabularnewline
110 & 164399 & 291580.9 & -127181.9 \tabularnewline
111 & 350667 & 245243.1875 & 105423.8125 \tabularnewline
112 & 303273 & 245243.1875 & 58029.8125 \tabularnewline
113 & 23623 & 45265.8235294118 & -21642.8235294118 \tabularnewline
114 & 195849 & 245243.1875 & -49394.1875 \tabularnewline
115 & 61857 & 45265.8235294118 & 16591.1764705882 \tabularnewline
116 & 184709 & 245243.1875 & -60534.1875 \tabularnewline
117 & 428191 & 386287.4 & 41903.6 \tabularnewline
118 & 21054 & 45265.8235294118 & -24211.8235294118 \tabularnewline
119 & 252805 & 205667.666666667 & 47137.3333333333 \tabularnewline
120 & 31961 & 45265.8235294118 & -13304.8235294118 \tabularnewline
121 & 351541 & 386287.4 & -34746.4 \tabularnewline
122 & 246359 & 205667.666666667 & 40691.3333333333 \tabularnewline
123 & 187003 & 205667.666666667 & -18664.6666666667 \tabularnewline
124 & 172442 & 205667.666666667 & -33225.6666666667 \tabularnewline
125 & 38214 & 45265.8235294118 & -7051.82352941176 \tabularnewline
126 & 241539 & 101530.857142857 & 140008.142857143 \tabularnewline
127 & 358276 & 291580.9 & 66695.1 \tabularnewline
128 & 209821 & 205667.666666667 & 4153.33333333334 \tabularnewline
129 & 441447 & 441469.875 & -22.875 \tabularnewline
130 & 348017 & 291580.9 & 56436.1 \tabularnewline
131 & 439634 & 386287.4 & 53346.6 \tabularnewline
132 & 208962 & 205667.666666667 & 3294.33333333334 \tabularnewline
133 & 105332 & 123447.571428571 & -18115.5714285714 \tabularnewline
134 & 311111 & 291580.9 & 19530.1 \tabularnewline
135 & 460033 & 441469.875 & 18563.125 \tabularnewline
136 & 159057 & 205667.666666667 & -46610.6666666667 \tabularnewline
137 & 411980 & 441469.875 & -29489.875 \tabularnewline
138 & 173486 & 205667.666666667 & -32181.6666666667 \tabularnewline
139 & 284582 & 245243.1875 & 39338.8125 \tabularnewline
140 & 283913 & 291580.9 & -7667.90000000002 \tabularnewline
141 & 234203 & 205667.666666667 & 28535.3333333333 \tabularnewline
142 & 386740 & 441469.875 & -54729.875 \tabularnewline
143 & 246963 & 245243.1875 & 1719.8125 \tabularnewline
144 & 173260 & 205667.666666667 & -32407.6666666667 \tabularnewline
145 & 346730 & 291580.9 & 55149.1 \tabularnewline
146 & 176654 & 245243.1875 & -68589.1875 \tabularnewline
147 & 259048 & 291580.9 & -32532.9 \tabularnewline
148 & 312540 & 291580.9 & 20959.1 \tabularnewline
149 & 1 & 291580.9 & -291579.9 \tabularnewline
150 & 14688 & 45265.8235294118 & -30577.8235294118 \tabularnewline
151 & 98 & 101530.857142857 & -101432.857142857 \tabularnewline
152 & 455 & 101530.857142857 & -101075.857142857 \tabularnewline
153 & 283222 & 245243.1875 & 37978.8125 \tabularnewline
154 & 409280 & 291580.9 & 117699.1 \tabularnewline
155 & 203 & 101530.857142857 & -101327.857142857 \tabularnewline
156 & 7199 & 45265.8235294118 & -38066.8235294118 \tabularnewline
157 & 46660 & 45265.8235294118 & 1394.17647058824 \tabularnewline
158 & 17547 & 45265.8235294118 & -27718.8235294118 \tabularnewline
159 & 121550 & 123447.571428571 & -1897.57142857143 \tabularnewline
160 & 969 & 101530.857142857 & -100561.857142857 \tabularnewline
161 & 242228 & 205667.666666667 & 36560.3333333333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159001&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]278691[/C][C]245243.1875[/C][C]33447.8125[/C][/ROW]
[ROW][C]2[/C][C]197623[/C][C]205667.666666667[/C][C]-8044.66666666666[/C][/ROW]
[ROW][C]3[/C][C]233139[/C][C]205667.666666667[/C][C]27471.3333333333[/C][/ROW]
[ROW][C]4[/C][C]221690[/C][C]291580.9[/C][C]-69890.9[/C][/ROW]
[ROW][C]5[/C][C]177540[/C][C]123447.571428571[/C][C]54092.4285714286[/C][/ROW]
[ROW][C]6[/C][C]70849[/C][C]45265.8235294118[/C][C]25583.1764705882[/C][/ROW]
[ROW][C]7[/C][C]566234[/C][C]441469.875[/C][C]124764.125[/C][/ROW]
[ROW][C]8[/C][C]33186[/C][C]45265.8235294118[/C][C]-12079.8235294118[/C][/ROW]
[ROW][C]9[/C][C]226511[/C][C]245243.1875[/C][C]-18732.1875[/C][/ROW]
[ROW][C]10[/C][C]245577[/C][C]101530.857142857[/C][C]144046.142857143[/C][/ROW]
[ROW][C]11[/C][C]317443[/C][C]291580.9[/C][C]25862.1[/C][/ROW]
[ROW][C]12[/C][C]248379[/C][C]245243.1875[/C][C]3135.8125[/C][/ROW]
[ROW][C]13[/C][C]200620[/C][C]205667.666666667[/C][C]-5047.66666666666[/C][/ROW]
[ROW][C]14[/C][C]367785[/C][C]291580.9[/C][C]76204.1[/C][/ROW]
[ROW][C]15[/C][C]266325[/C][C]245243.1875[/C][C]21081.8125[/C][/ROW]
[ROW][C]16[/C][C]394271[/C][C]441469.875[/C][C]-47198.875[/C][/ROW]
[ROW][C]17[/C][C]335567[/C][C]291580.9[/C][C]43986.1[/C][/ROW]
[ROW][C]18[/C][C]407650[/C][C]386287.4[/C][C]21362.6[/C][/ROW]
[ROW][C]19[/C][C]182016[/C][C]245243.1875[/C][C]-63227.1875[/C][/ROW]
[ROW][C]20[/C][C]267365[/C][C]245243.1875[/C][C]22121.8125[/C][/ROW]
[ROW][C]21[/C][C]279428[/C][C]291580.9[/C][C]-12152.9[/C][/ROW]
[ROW][C]22[/C][C]484574[/C][C]386287.4[/C][C]98286.6[/C][/ROW]
[ROW][C]23[/C][C]196721[/C][C]205667.666666667[/C][C]-8946.66666666666[/C][/ROW]
[ROW][C]24[/C][C]197899[/C][C]245243.1875[/C][C]-47344.1875[/C][/ROW]
[ROW][C]25[/C][C]256290[/C][C]386287.4[/C][C]-129997.4[/C][/ROW]
[ROW][C]26[/C][C]255126[/C][C]291580.9[/C][C]-36454.9[/C][/ROW]
[ROW][C]27[/C][C]281816[/C][C]291580.9[/C][C]-9764.90000000002[/C][/ROW]
[ROW][C]28[/C][C]278027[/C][C]245243.1875[/C][C]32783.8125[/C][/ROW]
[ROW][C]29[/C][C]173134[/C][C]205667.666666667[/C][C]-32533.6666666667[/C][/ROW]
[ROW][C]30[/C][C]383613[/C][C]386287.4[/C][C]-2674.40000000002[/C][/ROW]
[ROW][C]31[/C][C]302413[/C][C]291580.9[/C][C]10832.1[/C][/ROW]
[ROW][C]32[/C][C]251255[/C][C]205667.666666667[/C][C]45587.3333333333[/C][/ROW]
[ROW][C]33[/C][C]355456[/C][C]291580.9[/C][C]63875.1[/C][/ROW]
[ROW][C]34[/C][C]109546[/C][C]123447.571428571[/C][C]-13901.5714285714[/C][/ROW]
[ROW][C]35[/C][C]427915[/C][C]386287.4[/C][C]41627.6[/C][/ROW]
[ROW][C]36[/C][C]273950[/C][C]291580.9[/C][C]-17630.9[/C][/ROW]
[ROW][C]37[/C][C]427825[/C][C]386287.4[/C][C]41537.6[/C][/ROW]
[ROW][C]38[/C][C]247287[/C][C]205667.666666667[/C][C]41619.3333333333[/C][/ROW]
[ROW][C]39[/C][C]115658[/C][C]45265.8235294118[/C][C]70392.1764705882[/C][/ROW]
[ROW][C]40[/C][C]386534[/C][C]386287.4[/C][C]246.599999999977[/C][/ROW]
[ROW][C]41[/C][C]340132[/C][C]386287.4[/C][C]-46155.4[/C][/ROW]
[ROW][C]42[/C][C]194127[/C][C]205667.666666667[/C][C]-11540.6666666667[/C][/ROW]
[ROW][C]43[/C][C]213258[/C][C]245243.1875[/C][C]-31985.1875[/C][/ROW]
[ROW][C]44[/C][C]182398[/C][C]205667.666666667[/C][C]-23269.6666666667[/C][/ROW]
[ROW][C]45[/C][C]157164[/C][C]205667.666666667[/C][C]-48503.6666666667[/C][/ROW]
[ROW][C]46[/C][C]457592[/C][C]441469.875[/C][C]16122.125[/C][/ROW]
[ROW][C]47[/C][C]78800[/C][C]123447.571428571[/C][C]-44647.5714285714[/C][/ROW]
[ROW][C]48[/C][C]213831[/C][C]245243.1875[/C][C]-31412.1875[/C][/ROW]
[ROW][C]49[/C][C]368086[/C][C]386287.4[/C][C]-18201.4[/C][/ROW]
[ROW][C]50[/C][C]203104[/C][C]291580.9[/C][C]-88476.9[/C][/ROW]
[ROW][C]51[/C][C]244371[/C][C]245243.1875[/C][C]-872.1875[/C][/ROW]
[ROW][C]52[/C][C]24188[/C][C]45265.8235294118[/C][C]-21077.8235294118[/C][/ROW]
[ROW][C]53[/C][C]399093[/C][C]291580.9[/C][C]107512.1[/C][/ROW]
[ROW][C]54[/C][C]65029[/C][C]45265.8235294118[/C][C]19763.1764705882[/C][/ROW]
[ROW][C]55[/C][C]101097[/C][C]123447.571428571[/C][C]-22350.5714285714[/C][/ROW]
[ROW][C]56[/C][C]297973[/C][C]291580.9[/C][C]6392.09999999998[/C][/ROW]
[ROW][C]57[/C][C]352671[/C][C]245243.1875[/C][C]107427.8125[/C][/ROW]
[ROW][C]58[/C][C]367083[/C][C]386287.4[/C][C]-19204.4[/C][/ROW]
[ROW][C]59[/C][C]371178[/C][C]291580.9[/C][C]79597.1[/C][/ROW]
[ROW][C]60[/C][C]269973[/C][C]291580.9[/C][C]-21607.9[/C][/ROW]
[ROW][C]61[/C][C]389761[/C][C]386287.4[/C][C]3473.59999999998[/C][/ROW]
[ROW][C]62[/C][C]315924[/C][C]291580.9[/C][C]24343.1[/C][/ROW]
[ROW][C]63[/C][C]285807[/C][C]386287.4[/C][C]-100480.4[/C][/ROW]
[ROW][C]64[/C][C]282351[/C][C]291580.9[/C][C]-9229.90000000002[/C][/ROW]
[ROW][C]65[/C][C]250558[/C][C]205667.666666667[/C][C]44890.3333333333[/C][/ROW]
[ROW][C]66[/C][C]265696[/C][C]245243.1875[/C][C]20452.8125[/C][/ROW]
[ROW][C]67[/C][C]215915[/C][C]245243.1875[/C][C]-29328.1875[/C][/ROW]
[ROW][C]68[/C][C]247349[/C][C]291580.9[/C][C]-44231.9[/C][/ROW]
[ROW][C]69[/C][C]260919[/C][C]291580.9[/C][C]-30661.9[/C][/ROW]
[ROW][C]70[/C][C]182308[/C][C]245243.1875[/C][C]-62935.1875[/C][/ROW]
[ROW][C]71[/C][C]256761[/C][C]291580.9[/C][C]-34819.9[/C][/ROW]
[ROW][C]72[/C][C]73566[/C][C]45265.8235294118[/C][C]28300.1764705882[/C][/ROW]
[ROW][C]73[/C][C]263796[/C][C]245243.1875[/C][C]18552.8125[/C][/ROW]
[ROW][C]74[/C][C]207899[/C][C]245243.1875[/C][C]-37344.1875[/C][/ROW]
[ROW][C]75[/C][C]228779[/C][C]245243.1875[/C][C]-16464.1875[/C][/ROW]
[ROW][C]76[/C][C]363571[/C][C]291580.9[/C][C]71990.1[/C][/ROW]
[ROW][C]77[/C][C]382785[/C][C]386287.4[/C][C]-3502.40000000002[/C][/ROW]
[ROW][C]78[/C][C]220401[/C][C]205667.666666667[/C][C]14733.3333333333[/C][/ROW]
[ROW][C]79[/C][C]225097[/C][C]245243.1875[/C][C]-20146.1875[/C][/ROW]
[ROW][C]80[/C][C]215445[/C][C]245243.1875[/C][C]-29798.1875[/C][/ROW]
[ROW][C]81[/C][C]188786[/C][C]205667.666666667[/C][C]-16881.6666666667[/C][/ROW]
[ROW][C]82[/C][C]481148[/C][C]386287.4[/C][C]94860.6[/C][/ROW]
[ROW][C]83[/C][C]145943[/C][C]205667.666666667[/C][C]-59724.6666666667[/C][/ROW]
[ROW][C]84[/C][C]292287[/C][C]245243.1875[/C][C]47043.8125[/C][/ROW]
[ROW][C]85[/C][C]80953[/C][C]45265.8235294118[/C][C]35687.1764705882[/C][/ROW]
[ROW][C]86[/C][C]164260[/C][C]205667.666666667[/C][C]-41407.6666666667[/C][/ROW]
[ROW][C]87[/C][C]179344[/C][C]205667.666666667[/C][C]-26323.6666666667[/C][/ROW]
[ROW][C]88[/C][C]413462[/C][C]441469.875[/C][C]-28007.875[/C][/ROW]
[ROW][C]89[/C][C]358697[/C][C]291580.9[/C][C]67116.1[/C][/ROW]
[ROW][C]90[/C][C]180679[/C][C]291580.9[/C][C]-110901.9[/C][/ROW]
[ROW][C]91[/C][C]298696[/C][C]291580.9[/C][C]7115.09999999998[/C][/ROW]
[ROW][C]92[/C][C]288706[/C][C]245243.1875[/C][C]43462.8125[/C][/ROW]
[ROW][C]93[/C][C]197956[/C][C]205667.666666667[/C][C]-7711.66666666666[/C][/ROW]
[ROW][C]94[/C][C]282361[/C][C]291580.9[/C][C]-9219.90000000002[/C][/ROW]
[ROW][C]95[/C][C]329202[/C][C]205667.666666667[/C][C]123534.333333333[/C][/ROW]
[ROW][C]96[/C][C]221875[/C][C]101530.857142857[/C][C]120344.142857143[/C][/ROW]
[ROW][C]97[/C][C]277071[/C][C]245243.1875[/C][C]31827.8125[/C][/ROW]
[ROW][C]98[/C][C]305984[/C][C]291580.9[/C][C]14403.1[/C][/ROW]
[ROW][C]99[/C][C]416032[/C][C]386287.4[/C][C]29744.6[/C][/ROW]
[ROW][C]100[/C][C]412530[/C][C]386287.4[/C][C]26242.6[/C][/ROW]
[ROW][C]101[/C][C]297080[/C][C]291580.9[/C][C]5499.09999999998[/C][/ROW]
[ROW][C]102[/C][C]318235[/C][C]291580.9[/C][C]26654.1[/C][/ROW]
[ROW][C]103[/C][C]200486[/C][C]205667.666666667[/C][C]-5181.66666666666[/C][/ROW]
[ROW][C]104[/C][C]43287[/C][C]45265.8235294118[/C][C]-1978.82352941176[/C][/ROW]
[ROW][C]105[/C][C]189520[/C][C]245243.1875[/C][C]-55723.1875[/C][/ROW]
[ROW][C]106[/C][C]255152[/C][C]291580.9[/C][C]-36428.9[/C][/ROW]
[ROW][C]107[/C][C]288617[/C][C]386287.4[/C][C]-97670.4[/C][/ROW]
[ROW][C]108[/C][C]314167[/C][C]291580.9[/C][C]22586.1[/C][/ROW]
[ROW][C]109[/C][C]170268[/C][C]123447.571428571[/C][C]46820.4285714286[/C][/ROW]
[ROW][C]110[/C][C]164399[/C][C]291580.9[/C][C]-127181.9[/C][/ROW]
[ROW][C]111[/C][C]350667[/C][C]245243.1875[/C][C]105423.8125[/C][/ROW]
[ROW][C]112[/C][C]303273[/C][C]245243.1875[/C][C]58029.8125[/C][/ROW]
[ROW][C]113[/C][C]23623[/C][C]45265.8235294118[/C][C]-21642.8235294118[/C][/ROW]
[ROW][C]114[/C][C]195849[/C][C]245243.1875[/C][C]-49394.1875[/C][/ROW]
[ROW][C]115[/C][C]61857[/C][C]45265.8235294118[/C][C]16591.1764705882[/C][/ROW]
[ROW][C]116[/C][C]184709[/C][C]245243.1875[/C][C]-60534.1875[/C][/ROW]
[ROW][C]117[/C][C]428191[/C][C]386287.4[/C][C]41903.6[/C][/ROW]
[ROW][C]118[/C][C]21054[/C][C]45265.8235294118[/C][C]-24211.8235294118[/C][/ROW]
[ROW][C]119[/C][C]252805[/C][C]205667.666666667[/C][C]47137.3333333333[/C][/ROW]
[ROW][C]120[/C][C]31961[/C][C]45265.8235294118[/C][C]-13304.8235294118[/C][/ROW]
[ROW][C]121[/C][C]351541[/C][C]386287.4[/C][C]-34746.4[/C][/ROW]
[ROW][C]122[/C][C]246359[/C][C]205667.666666667[/C][C]40691.3333333333[/C][/ROW]
[ROW][C]123[/C][C]187003[/C][C]205667.666666667[/C][C]-18664.6666666667[/C][/ROW]
[ROW][C]124[/C][C]172442[/C][C]205667.666666667[/C][C]-33225.6666666667[/C][/ROW]
[ROW][C]125[/C][C]38214[/C][C]45265.8235294118[/C][C]-7051.82352941176[/C][/ROW]
[ROW][C]126[/C][C]241539[/C][C]101530.857142857[/C][C]140008.142857143[/C][/ROW]
[ROW][C]127[/C][C]358276[/C][C]291580.9[/C][C]66695.1[/C][/ROW]
[ROW][C]128[/C][C]209821[/C][C]205667.666666667[/C][C]4153.33333333334[/C][/ROW]
[ROW][C]129[/C][C]441447[/C][C]441469.875[/C][C]-22.875[/C][/ROW]
[ROW][C]130[/C][C]348017[/C][C]291580.9[/C][C]56436.1[/C][/ROW]
[ROW][C]131[/C][C]439634[/C][C]386287.4[/C][C]53346.6[/C][/ROW]
[ROW][C]132[/C][C]208962[/C][C]205667.666666667[/C][C]3294.33333333334[/C][/ROW]
[ROW][C]133[/C][C]105332[/C][C]123447.571428571[/C][C]-18115.5714285714[/C][/ROW]
[ROW][C]134[/C][C]311111[/C][C]291580.9[/C][C]19530.1[/C][/ROW]
[ROW][C]135[/C][C]460033[/C][C]441469.875[/C][C]18563.125[/C][/ROW]
[ROW][C]136[/C][C]159057[/C][C]205667.666666667[/C][C]-46610.6666666667[/C][/ROW]
[ROW][C]137[/C][C]411980[/C][C]441469.875[/C][C]-29489.875[/C][/ROW]
[ROW][C]138[/C][C]173486[/C][C]205667.666666667[/C][C]-32181.6666666667[/C][/ROW]
[ROW][C]139[/C][C]284582[/C][C]245243.1875[/C][C]39338.8125[/C][/ROW]
[ROW][C]140[/C][C]283913[/C][C]291580.9[/C][C]-7667.90000000002[/C][/ROW]
[ROW][C]141[/C][C]234203[/C][C]205667.666666667[/C][C]28535.3333333333[/C][/ROW]
[ROW][C]142[/C][C]386740[/C][C]441469.875[/C][C]-54729.875[/C][/ROW]
[ROW][C]143[/C][C]246963[/C][C]245243.1875[/C][C]1719.8125[/C][/ROW]
[ROW][C]144[/C][C]173260[/C][C]205667.666666667[/C][C]-32407.6666666667[/C][/ROW]
[ROW][C]145[/C][C]346730[/C][C]291580.9[/C][C]55149.1[/C][/ROW]
[ROW][C]146[/C][C]176654[/C][C]245243.1875[/C][C]-68589.1875[/C][/ROW]
[ROW][C]147[/C][C]259048[/C][C]291580.9[/C][C]-32532.9[/C][/ROW]
[ROW][C]148[/C][C]312540[/C][C]291580.9[/C][C]20959.1[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]291580.9[/C][C]-291579.9[/C][/ROW]
[ROW][C]150[/C][C]14688[/C][C]45265.8235294118[/C][C]-30577.8235294118[/C][/ROW]
[ROW][C]151[/C][C]98[/C][C]101530.857142857[/C][C]-101432.857142857[/C][/ROW]
[ROW][C]152[/C][C]455[/C][C]101530.857142857[/C][C]-101075.857142857[/C][/ROW]
[ROW][C]153[/C][C]283222[/C][C]245243.1875[/C][C]37978.8125[/C][/ROW]
[ROW][C]154[/C][C]409280[/C][C]291580.9[/C][C]117699.1[/C][/ROW]
[ROW][C]155[/C][C]203[/C][C]101530.857142857[/C][C]-101327.857142857[/C][/ROW]
[ROW][C]156[/C][C]7199[/C][C]45265.8235294118[/C][C]-38066.8235294118[/C][/ROW]
[ROW][C]157[/C][C]46660[/C][C]45265.8235294118[/C][C]1394.17647058824[/C][/ROW]
[ROW][C]158[/C][C]17547[/C][C]45265.8235294118[/C][C]-27718.8235294118[/C][/ROW]
[ROW][C]159[/C][C]121550[/C][C]123447.571428571[/C][C]-1897.57142857143[/C][/ROW]
[ROW][C]160[/C][C]969[/C][C]101530.857142857[/C][C]-100561.857142857[/C][/ROW]
[ROW][C]161[/C][C]242228[/C][C]205667.666666667[/C][C]36560.3333333333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159001&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159001&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
#	Actuals	Forecasts	Residuals
1	278691	245243.1875	33447.8125
2	197623	205667.666666667	-8044.66666666666
3	233139	205667.666666667	27471.3333333333
4	221690	291580.9	-69890.9
5	177540	123447.571428571	54092.4285714286
6	70849	45265.8235294118	25583.1764705882
7	566234	441469.875	124764.125
8	33186	45265.8235294118	-12079.8235294118
9	226511	245243.1875	-18732.1875
10	245577	101530.857142857	144046.142857143
11	317443	291580.9	25862.1
12	248379	245243.1875	3135.8125
13	200620	205667.666666667	-5047.66666666666
14	367785	291580.9	76204.1
15	266325	245243.1875	21081.8125
16	394271	441469.875	-47198.875
17	335567	291580.9	43986.1
18	407650	386287.4	21362.6
19	182016	245243.1875	-63227.1875
20	267365	245243.1875	22121.8125
21	279428	291580.9	-12152.9
22	484574	386287.4	98286.6
23	196721	205667.666666667	-8946.66666666666
24	197899	245243.1875	-47344.1875
25	256290	386287.4	-129997.4
26	255126	291580.9	-36454.9
27	281816	291580.9	-9764.90000000002
28	278027	245243.1875	32783.8125
29	173134	205667.666666667	-32533.6666666667
30	383613	386287.4	-2674.40000000002
31	302413	291580.9	10832.1
32	251255	205667.666666667	45587.3333333333
33	355456	291580.9	63875.1
34	109546	123447.571428571	-13901.5714285714
35	427915	386287.4	41627.6
36	273950	291580.9	-17630.9
37	427825	386287.4	41537.6
38	247287	205667.666666667	41619.3333333333
39	115658	45265.8235294118	70392.1764705882
40	386534	386287.4	246.599999999977
41	340132	386287.4	-46155.4
42	194127	205667.666666667	-11540.6666666667
43	213258	245243.1875	-31985.1875
44	182398	205667.666666667	-23269.6666666667
45	157164	205667.666666667	-48503.6666666667
46	457592	441469.875	16122.125
47	78800	123447.571428571	-44647.5714285714
48	213831	245243.1875	-31412.1875
49	368086	386287.4	-18201.4
50	203104	291580.9	-88476.9
51	244371	245243.1875	-872.1875
52	24188	45265.8235294118	-21077.8235294118
53	399093	291580.9	107512.1
54	65029	45265.8235294118	19763.1764705882
55	101097	123447.571428571	-22350.5714285714
56	297973	291580.9	6392.09999999998
57	352671	245243.1875	107427.8125
58	367083	386287.4	-19204.4
59	371178	291580.9	79597.1
60	269973	291580.9	-21607.9
61	389761	386287.4	3473.59999999998
62	315924	291580.9	24343.1
63	285807	386287.4	-100480.4
64	282351	291580.9	-9229.90000000002
65	250558	205667.666666667	44890.3333333333
66	265696	245243.1875	20452.8125
67	215915	245243.1875	-29328.1875
68	247349	291580.9	-44231.9
69	260919	291580.9	-30661.9
70	182308	245243.1875	-62935.1875
71	256761	291580.9	-34819.9
72	73566	45265.8235294118	28300.1764705882
73	263796	245243.1875	18552.8125
74	207899	245243.1875	-37344.1875
75	228779	245243.1875	-16464.1875
76	363571	291580.9	71990.1
77	382785	386287.4	-3502.40000000002
78	220401	205667.666666667	14733.3333333333
79	225097	245243.1875	-20146.1875
80	215445	245243.1875	-29798.1875
81	188786	205667.666666667	-16881.6666666667
82	481148	386287.4	94860.6
83	145943	205667.666666667	-59724.6666666667
84	292287	245243.1875	47043.8125
85	80953	45265.8235294118	35687.1764705882
86	164260	205667.666666667	-41407.6666666667
87	179344	205667.666666667	-26323.6666666667
88	413462	441469.875	-28007.875
89	358697	291580.9	67116.1
90	180679	291580.9	-110901.9
91	298696	291580.9	7115.09999999998
92	288706	245243.1875	43462.8125
93	197956	205667.666666667	-7711.66666666666
94	282361	291580.9	-9219.90000000002
95	329202	205667.666666667	123534.333333333
96	221875	101530.857142857	120344.142857143
97	277071	245243.1875	31827.8125
98	305984	291580.9	14403.1
99	416032	386287.4	29744.6
100	412530	386287.4	26242.6
101	297080	291580.9	5499.09999999998
102	318235	291580.9	26654.1
103	200486	205667.666666667	-5181.66666666666
104	43287	45265.8235294118	-1978.82352941176
105	189520	245243.1875	-55723.1875
106	255152	291580.9	-36428.9
107	288617	386287.4	-97670.4
108	314167	291580.9	22586.1
109	170268	123447.571428571	46820.4285714286
110	164399	291580.9	-127181.9
111	350667	245243.1875	105423.8125
112	303273	245243.1875	58029.8125
113	23623	45265.8235294118	-21642.8235294118
114	195849	245243.1875	-49394.1875
115	61857	45265.8235294118	16591.1764705882
116	184709	245243.1875	-60534.1875
117	428191	386287.4	41903.6
118	21054	45265.8235294118	-24211.8235294118
119	252805	205667.666666667	47137.3333333333
120	31961	45265.8235294118	-13304.8235294118
121	351541	386287.4	-34746.4
122	246359	205667.666666667	40691.3333333333
123	187003	205667.666666667	-18664.6666666667
124	172442	205667.666666667	-33225.6666666667
125	38214	45265.8235294118	-7051.82352941176
126	241539	101530.857142857	140008.142857143
127	358276	291580.9	66695.1
128	209821	205667.666666667	4153.33333333334
129	441447	441469.875	-22.875
130	348017	291580.9	56436.1
131	439634	386287.4	53346.6
132	208962	205667.666666667	3294.33333333334
133	105332	123447.571428571	-18115.5714285714
134	311111	291580.9	19530.1
135	460033	441469.875	18563.125
136	159057	205667.666666667	-46610.6666666667
137	411980	441469.875	-29489.875
138	173486	205667.666666667	-32181.6666666667
139	284582	245243.1875	39338.8125
140	283913	291580.9	-7667.90000000002
141	234203	205667.666666667	28535.3333333333
142	386740	441469.875	-54729.875
143	246963	245243.1875	1719.8125
144	173260	205667.666666667	-32407.6666666667
145	346730	291580.9	55149.1
146	176654	245243.1875	-68589.1875
147	259048	291580.9	-32532.9
148	312540	291580.9	20959.1
149	1	291580.9	-291579.9
150	14688	45265.8235294118	-30577.8235294118
151	98	101530.857142857	-101432.857142857
152	455	101530.857142857	-101075.857142857
153	283222	245243.1875	37978.8125
154	409280	291580.9	117699.1
155	203	101530.857142857	-101327.857142857
156	7199	45265.8235294118	-38066.8235294118
157	46660	45265.8235294118	1394.17647058824
158	17547	45265.8235294118	-27718.8235294118
159	121550	123447.571428571	-1897.57142857143
160	969	101530.857142857	-100561.857142857
161	242228	205667.666666667	36560.3333333333

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = pearson ;

Parameters (R input):

par1 = 1 ; par2 = none ; par3 = ; 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code