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Author's title

Author*Unverified author*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationSun, 02 Dec 2012 07:55:42 -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/02/t1354453059rhxzix6qkyz7ene.htm/, Retrieved Thu, 31 Oct 2024 23:50:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195476, Retrieved Thu, 31 Oct 2024 23:50:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact193
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Linear Regression Graphical Model Validation] [Colombia Coffee -...] [2008-02-26 10:22:06] [74be16979710d4c4e7c6647856088456]
- RM D    [Linear Regression Graphical Model Validation] [simple regression...] [2012-12-02 12:55:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D      [Linear Regression Graphical Model Validation] [lineair regressio...] [2012-12-02 13:14:50] [74be16979710d4c4e7c6647856088456]
-    D        [Linear Regression Graphical Model Validation] [simple lineair re...] [2012-12-02 14:14:16] [74be16979710d4c4e7c6647856088456]
-    D        [Linear Regression Graphical Model Validation] [] [2014-12-03 14:41:24] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
210907
120982
176508
179321
123185
52746
385534
33170
101645
149061
165446
237213
173326
133131
258873
180083
324799
230964
236785
135473
202925
215147
344297
153935
132943
174724
174415
225548
223632
124817
221698
210767
170266
260561
84853
294424
101011
215641
325107
7176
167542
106408
96560
265769
269651
149112
175824
152871
111665
116408
362301
78800
183167
277965
150629
168809
24188
329267
65029
101097
218946
244052
341570
103597
233328
256462
206161
311473
235800
177939
207176
196553
174184
143246
187559
187681
119016
182192
73566
194979
167488
143756
275541
243199
182999
135649
152299
120221
346485
145790
193339
80953
122774
130585
112611
286468
241066
148446
204713
182079
140344
220516
243060
162765
182613
232138
265318
85574
310839
225060
232317
144966
43287
155754
164709
201940
235454
220801
99466
92661
133328
61361
125930
100750
224549
82316
102010
101523
243511
22938
41566
152474
61857
99923
132487
317394
21054
209641
22648
31414
46698
131698
91735
244749
184510
79863
128423
97839
38214
151101
272458
172494
108043
328107
250579
351067
158015
98866
85439
229242
351619
84207
120445
324598
131069
204271
165543
141722
116048
250047
299775
195838
173260
254488
104389
136084
199476
92499
224330
135781
74408
81240
14688
181633
271856
7199
46660
17547
133368
95227
152601
98146
79619
59194
139942
118612
72880
65475
99643
71965
77272
49289
135131
108446
89746
44296
77648
181528
134019
124064
92630
121848
52915
81872
58981
53515
60812
56375
65490
80949
76302
104011
98104
67989
30989
135458
73504
63123
61254
74914
31774
81437
87186
50090
65745
56653
158399
46455
73624
38395
91899
139526
52164
51567
70551
84856
102538
86678
85709
34662
150580
99611
19349
99373
86230
30837
31706
89806
62088
40151
27634
76990
37460
54157
49862
84337
64175
59382
119308
76702
103425
70344
43410
104838
62215
69304
53117
19764
86680
84105
77945
89113
91005
40248
64187
50857
56613
62792
72535
Dataseries Y:
56
56
54
89
40
25
92
18
63
44
33
84
88
55
60
66
154
53
119
41
61
58
75
33
40
92
100
112
73
40
45
60
62
75
31
77
34
46
99
17
66
30
76
146
67
56
107
58
34
61
119
42
66
89
44
66
24
259
17
64
41
68
168
43
132
105
71
112
94
82
70
57
53
103
121
62
52
52
32
62
45
46
63
75
88
46
53
37
90
63
78
25
45
46
41
144
82
91
71
63
53
62
63
32
39
62
117
34
92
93
54
144
14
61
109
38
73
75
50
61
55
77
75
72
50
32
53
42
71
10
35
65
25
66
41
86
16
42
19
19
45
65
35
95
49
37
64
38
34
32
65
52
62
65
83
95
29
18
33
247
139
29
118
110
67
42
65
94
64
81
95
67
63
83
45
30
70
32
83
31
67
66
10
70
103
5
20
5
36
34
48
40
43
31
42
46
33
18
55
35
59
19
66
60
36
25
47
54
53
40
40
39
14
45
36
28
44
30
22
17
31
55
54
21
14
81
35
43
46
30
23
38
54
20
53
45
39
20
24
31
35
151
52
30
31
29
57
40
44
25
77
35
11
63
44
19
13
42
38
29
20
27
20
19
37
26
42
49
30
49
67
28
19
49
27
30
22
12
31
20
20
39
29
16
27
21
19
35
14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 7 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195476&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195476&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 time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term14.20395991800352.724097354416375.214189535104433.53823967680356e-07
slope0.0002945078291702541.69514004761485e-0517.37365768596180

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 14.2039599180035 & 2.72409735441637 & 5.21418953510443 & 3.53823967680356e-07 \tabularnewline
slope & 0.000294507829170254 & 1.69514004761485e-05 & 17.3736576859618 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195476&T=1

[TABLE]
[ROW][C]Simple Linear Regression[/C][/ROW]
[ROW][C]Statistics[/C][C]Estimate[/C][C]S.D.[/C][C]T-STAT (H0: coeff=0)[/C][C]P-value (two-sided)[/C][/ROW]
[ROW][C]constant term[/C][C]14.2039599180035[/C][C]2.72409735441637[/C][C]5.21418953510443[/C][C]3.53823967680356e-07[/C][/ROW]
[ROW][C]slope[/C][C]0.000294507829170254[/C][C]1.69514004761485e-05[/C][C]17.3736576859618[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195476&T=1

As an alternative you can also use a QR Code:  

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

Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term14.20395991800352.724097354416375.214189535104433.53823967680356e-07
slope0.0002945078291702541.69514004761485e-0517.37365768596180



Parameters (Session):
par1 = 0 ;
Parameters (R input):
par1 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
library(lattice)
z <- as.data.frame(cbind(x,y))
m <- lm(y~x)
summary(m)
bitmap(file='test1.png')
plot(z,main='Scatterplot, lowess, and regression line')
lines(lowess(z),col='red')
abline(m)
grid()
dev.off()
bitmap(file='test2.png')
m2 <- lm(m$fitted.values ~ x)
summary(m2)
z2 <- as.data.frame(cbind(x,m$fitted.values))
names(z2) <- list('x','Fitted')
plot(z2,main='Scatterplot, lowess, and regression line')
lines(lowess(z2),col='red')
abline(m2)
grid()
dev.off()
bitmap(file='test3.png')
m3 <- lm(m$residuals ~ x)
summary(m3)
z3 <- as.data.frame(cbind(x,m$residuals))
names(z3) <- list('x','Residuals')
plot(z3,main='Scatterplot, lowess, and regression line')
lines(lowess(z3),col='red')
abline(m3)
grid()
dev.off()
bitmap(file='test4.png')
m4 <- lm(m$fitted.values ~ m$residuals)
summary(m4)
z4 <- as.data.frame(cbind(m$residuals,m$fitted.values))
names(z4) <- list('Residuals','Fitted')
plot(z4,main='Scatterplot, lowess, and regression line')
lines(lowess(z4),col='red')
abline(m4)
grid()
dev.off()
bitmap(file='test5.png')
myr <- as.ts(m$residuals)
z5 <- as.data.frame(cbind(lag(myr,1),myr))
names(z5) <- list('Lagged Residuals','Residuals')
plot(z5,main='Lag plot')
m5 <- lm(z5)
summary(m5)
abline(m5)
grid()
dev.off()
bitmap(file='test6.png')
hist(m$residuals,main='Residual Histogram',xlab='Residuals')
dev.off()
bitmap(file='test7.png')
if (par1 > 0)
{
densityplot(~m$residuals,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~m$residuals,col='black',main='Density Plot')
}
dev.off()
bitmap(file='test8.png')
acf(m$residuals,main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test9.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Simple Linear Regression',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistics',1,TRUE)
a<-table.element(a,'Estimate',1,TRUE)
a<-table.element(a,'S.D.',1,TRUE)
a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE)
a<-table.element(a,'P-value (two-sided)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'constant term',header=TRUE)
a<-table.element(a,m$coefficients[[1]])
sd <- sqrt(vcov(m)[1,1])
a<-table.element(a,sd)
tstat <- m$coefficients[[1]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'slope',header=TRUE)
a<-table.element(a,m$coefficients[[2]])
sd <- sqrt(vcov(m)[2,2])
a<-table.element(a,sd)
tstat <- m$coefficients[[2]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')