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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationWed, 03 Dec 2014 14:41:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/03/t1417619337m4cjwtnfkov7flj.htm/, Retrieved Tue, 07 May 2024 20:52:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262966, Retrieved Tue, 07 May 2024 20:52:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

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] [74be16979710d4c4e7c6647856088456]
-    D    [Linear Regression Graphical Model Validation] [lineair regressio...] [2012-12-02 13:14:50] [74be16979710d4c4e7c6647856088456]
-    D        [Linear Regression Graphical Model Validation] [] [2014-12-03 14:41:24] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
122788
220223
252275
248600
522089
84296
431397
530587
775158
84748
300801
107476
277604
164892
217926
641548
575130
205486
152589
586263
271763
339667
162822
281190
167894
103963
349511
417211
116672
181697
425816
236957
172023
310697
321055
274870
140595
269876
204783
257548
216809
390873
273932
232910
143824
208855
442975
255597
366334
286294
350044
164314
333116
70154
505048
279292
352129
144191
288411
272522
284231
311762
342350
177034
177034
289214
309277
246966
284308
187677
432628
246861
337931
260080
154768
314379
186002
255530
219180
182739
180278
240123
109044
251742
187742
270639
314020
246900
259062
282775
435991
154022
209685
205255
178265
248450
229320
135198
189190
322752
343956
176243
200373
366805
142330
360464
242381
281597
223788
199650
210891
343904
309815
137236
153390
82255
278265
172064
93154
326462
338105
224385
265772
409332
188407
229350
112000
136760
96105
378514
231662
222959
232819
208477
273205
505048
174313
243623
288700
254403
272544
225506
166212
192335
266657
250471
281982
201041
358421
185187
186000
368617
281639
279292
199645
352460
273205
261363
169170
161602
298581
217240
172437
178344
202510
278377
328714
273244
244625
267828
105343
Dataseries Y:
Download CSV
Histogram 
0,5
7,5
9
9,5
8,5
7
8
10
7
8,5
9
9,5
4
6
8
5,5
9,5
7,5
7
7,5
8
7
7
6
10
2,5
9
8
6
8,5
6
9
8
8
9
5,5
5
7
5,5
9
2
8,5
9
8,5
9
7,5
10
9
7,5
6
10,5
8,5
8
10
10,5
6,5
9,5
8,5
7,5
5
8
10
7
7,5
7,5
9,5
6
10
7
3
6
7
10
7
3,5
8
10
5,5
6
6,5
6,5
8,5
4
9,5
8
8,5
5,5
7
9
8
10
8
6
8
5
9
4,5
8,5
7
9,5
8,5
7,5
7,5
5
7
8
5,5
8,5
7,5
9,5
7
8
8,5
3,5
6,5
6,5
10,5
8,5
8
10
10
9,5
9
10
7,5
4,5
4,5
0,5
6,5
4,5
5,5
5
6
4
8
10,5
8,5
6,5
8
8,5
5,5
7
5
3,5
5
9
8,5
5
9,5
3
1,5
6
0,5
6,5
7,5
4,5
8
9
7,5
8,5
7
9,5
6,5
9,5
6
8
9,5
8
8
9
5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262966&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262966&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262966&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.wessa.net






Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term5.9674865278160.40000537328399514.9185159159830
slope5.08117421588393e-061.42958968045616e-063.554288538416560.000491586586086612

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 5.967486527816 & 0.400005373283995 & 14.918515915983 & 0 \tabularnewline
slope & 5.08117421588393e-06 & 1.42958968045616e-06 & 3.55428853841656 & 0.000491586586086612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262966&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]5.967486527816[/C][C]0.400005373283995[/C][C]14.918515915983[/C][C]0[/C][/ROW]
[ROW][C]slope[/C][C]5.08117421588393e-06[/C][C]1.42958968045616e-06[/C][C]3.55428853841656[/C][C]0.000491586586086612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262966&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262966&T=1

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


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

Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term5.9674865278160.40000537328399514.9185159159830
slope5.08117421588393e-061.42958968045616e-063.554288538416560.000491586586086612


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Input Parameters & R Code

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')