FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationThu, 04 Dec 2014 16:24:45 +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/04/t14177103111l1f16wu93mf1ke.htm/, Retrieved Thu, 16 May 2024 20:04:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263341, Retrieved Thu, 16 May 2024 20:04:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

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]
- R  D  [Linear Regression Graphical Model Validation] [assignment 3] [2014-10-30 12:05:05] [b41fa3f8b03b9633b409fd88ca7bde23]
- R  D    [Linear Regression Graphical Model Validation] [Simple Linear Reg...] [2014-12-04 16:06:22] [b54f62a7fd1df3c2be93114d7438324b]
-    D        [Linear Regression Graphical Model Validation] [Simple Linear Reg...] [2014-12-04 16:24:45] [310e7528d8f6aa5642dc98f4186768d1] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4
6
5
6
5
4
0
5
3
5
2
3
4
6
3
4
1
5
4
4
4
3
6
5
5
6
4
6
5
6
5
4
4
6
6
4
6
6
3
4
5
6
6
6
6
6
5
5
3
5
1
5
6
6
4
6
6
6
5
2
2
6
6
5
6
5
4
5
4
5
4
6
5
4
5
5
6
4
6
2
5
6
5
5
3
3
5
6
2
6
4
5
6
5
5
6
5
6
5
4
5
5
5
5
4
5
0
5
6
1
1
3
3
6
4
5
6
6
6
6
6
6
5
6
5
6
5
5
6
4
5
6
6
5
6
6
6
4
6
5
6
6
5
4
5
6
0
6
4
6
4
6
4
5
1
5
5
5
5
5
6
5
6
5
6
5
6
5
5
6
6
6
6
6
6
6
6
5
6
6
6
6
5
3
4
6
4
6
6
3
4
4
4
4
4
4
6
4
4
2
5
6
6
1
4
5
5
6
5
6
6
5
5
6
4
0
6
5
6
2
5
5
1
5
4
5
4
6
5
6
6
6
6
5
6
5
5
5
0
6
6
6
0
5
5
5
0
4
6
4
5
6
5
6
6
5
5
6
6
6
4
5
2
6
6
4
6
5
4
6
6
1
5
5
6
4
3
4
5
5
6
1
6
4
4
5
3
6
2
6
6
5
6
6
6
6
2
5
6
4
5
5
4
6
6
5
6
5
6
6
2
5
5
6
4
6
6
6
5
3
6
4
6
4
6
5
4
6
0
4
5
4
5
5
4
5
2
6
2
4
5
3
2
6
3
6
5
5
6
5
5
5
5
5
6
5
6
4
5
5
6
6
3
6
4
5
6
6
5
5
5
4
1
5
5
4
5
6
4
5
6
4
6
4
4
6
4
5
4
6
6
5
6
6
4
5
6
6
6
6
6
6
6
6
6
4
0
6
5
5
6
5
2
6
6
4
4
6
5
6
6
5
3
4
5
6
6
5
6
6
5
5
6
4
4
1
5
5
6
3
4
5
2
6
1
6
6
6
5
2
1
4
6
5
3
4
5
4
4
5
5
6
6
3
4
5
3
5
5
6
6
2
6
5
4
6
3
5
6
5
6
4
6
6
4
6
4
5
5
4
4
5
2
6
6
4
1
6
5
6
6
6
6
6
6
6
4
4
5
0
4
4
2
6
3
5
4
5
6
4
6
3
5
3
5
5
4
5
5
5
5
4
6
5
5
6
6
4
5
4
6
4
4
2
5
4
4
3
2
6
4
4
3
1
5
6
4
5
4
3
5
6
5
5
5
1
4
6
4
3
5
5
5
5
4
5
6
4
6
6
4
6
4
5
2
2
2
5
4
6
5
6
5
6
5
6
6
2
5
6
4
6
6
3
6
4
6
5
4
6
5
6
2
6
3
6
4
5
3
6
4
4
3
3
3
5
5
5
4
2
6
4
4
5
4
3
6
5
1
3
3
3
4
4
6
6
5
2
0
3
5
5
4
5
6
3
5
6
1
4
4
1
2
6
6
5
5
6
6
4
5
1
5
5
3
3
6
5
6
5
0
6
5
5
5
5
2
5
5
5
3
4
6
3
2
6
5
3
5
5
4
6
3
3
4
4
3
6
5
4
4
5
6
5
4
5
3
5
5
5
5
4
5
6
5
5
6
4
4
3
Dataseries Y:
Download CSV
Histogram 
21
26
22
22
18
23
12
20
22
21
19
22
15
20
19
18
15
20
21
21
15
16
23
21
18
25
9
30
20
23
16
16
19
25
25
18
23
21
10
14
22
26
23
23
24
24
18
23
15
19
16
25
23
17
19
21
18
27
21
13
8
29
28
23
21
19
19
20
18
19
17
19
25
19
22
23
26
14
28
16
24
20
12
24
22
12
22
20
10
23
17
22
24
18
21
20
20
22
19
20
26
23
24
21
21
19
8
17
20
11
8
15
18
18
19
19
23
22
21
25
30
17
27
23
23
18
18
23
19
15
20
16
24
25
25
19
19
16
19
19
23
21
22
19
20
20
3
23
14
23
20
15
13
16
7
24
17
24
24
19
25
20
28
23
27
18
28
21
19
23
27
22
28
25
21
22
28
20
29
25
25
20
20
16
20
20
23
18
25
18
19
25
25
25
24
19
26
10
17
13
17
30
25
4
16
21
23
22
17
20
20
22
16
23
16
0
18
25
23
12
18
24
11
18
14
23
24
29
18
15
29
16
19
22
16
23
23
19
4
20
24
20
4
24
22
16
3
15
24
17
20
27
23
26
23
17
20
22
19
24
19
23
15
27
26
22
22
18
15
22
27
10
20
17
23
19
13
27
23
16
25
2
26
20
23
22
24
22
17
23
23
28
29
21
24
20
7
19
28
18
26
21
19
20
23
24
16
19
24
21
16
16
21
28
16
23
26
29
18
19
19
16
16
16
18
22
14
20
15
22
24
16
19
24
19
15
11
15
17
20
21
16
17
20
15
21
16
18
25
21
21
16
20
24
28
27
22
20
27
17
22
23
15
22
13
21
18
22
19
15
20
17
21
23
20
18
22
24
24
18
27
19
20
15
20
27
20
20
13
21
23
26
24
25
18
21
23
16
19
20
25
22
20
25
27
20
18
26
26
24
27
16
15
25
27
18
16
18
23
21
21
14
24
18
16
25
22
13
20
17
23
22
23
22
23
10
18
25
26
14
23
22
23
19
14
26
24
21
17
16
15
11
19
21
20
16
19
16
11
22
20
26
26
20
24
20
15
23
25
27
23
20
25
24
22
27
20
17
22
26
19
19
24
22
16
22
23
19
20
16
19
20
15
22
22
12
15
21
26
27
23
21
22
26
24
27
18
18
25
12
19
24
17
22
15
20
24
17
24
15
20
20
17
11
21
28
14
13
12
21
13
19
23
27
25
22
27
16
20
18
19
17
10
11
16
13
14
12
15
19
15
14
14
10
13
21
11
14
20
7
22
24
16
22
25
5
19
23
13
10
12
21
22
20
17
20
13
9
22
15
12
25
14
14
17
9
10
15
15
15
14
21
13
18
20
16
28
12
20
26
18
21
23
13
22
14
23
16
14
22
19
23
16
20
8
16
11
16
10
17
16
17
10
15
13
19
14
18
25
10
22
15
18
22
18
15
20
18
6
17
12
12
19
23
26
28
19
16
3
11
15
22
12
21
25
12
14
24
12
13
15
17
12
28
25
14
21
18
23
16
15
5
19
22
19
12
22
18
24
19
4
20
24
26
22
19
9
22
18
16
19
20
21
17
9
26
28
13
16
22
18
21
10
15
15
13
10
23
21
14
17
15
15
17
26
12
14
26
18
17
20
16
19
12
20
19
25
19
15
12

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'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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263341&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263341&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263341&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term8.057835885216870.48071117779424616.76232269486730
slope2.414355159376210.098524843648892224.50503923639930

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 8.05783588521687 & 0.480711177794246 & 16.7623226948673 & 0 \tabularnewline
slope & 2.41435515937621 & 0.0985248436488922 & 24.5050392363993 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263341&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]8.05783588521687[/C][C]0.480711177794246[/C][C]16.7623226948673[/C][C]0[/C][/ROW]
[ROW][C]slope[/C][C]2.41435515937621[/C][C]0.0985248436488922[/C][C]24.5050392363993[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263341&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263341&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 term8.057835885216870.48071117779424616.76232269486730
slope2.414355159376210.098524843648892224.50503923639930


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


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')