## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationMon, 07 Nov 2011 14:33:53 -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/2011/Nov/07/t1320694459ta1igamk450wegk.htm/, Retrieved Thu, 07 Dec 2023 02:43:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=140356, Retrieved Thu, 07 Dec 2023 02:43:10 +0000
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User-defined keywords
Estimated Impact142
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-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-01 13:37:53] [b98453cac15ba1066b407e146608df68]
-   P   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-07 18:14:56] [aefb5c2d4042694c5b6b82f93ac1885a]
-           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-07 19:33:53] [2be7aedefc35278abdba659ba29c8de8] [Current]
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Dataseries X:
1	1	4	0	2	'T'	0	3	-1	1	4
1	1	0	0	2	'T'	0	-1	-1	1	0
0	1	4	1	1.5	'T'	1	4	1	1.5	5
0	0	0	0	0	'T'	0	0	0	0	0
1	1	0	1	1	'T'	0	-1	0	0	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	0	1	2	'T'	0	-1	0	1	0
0	1	0	1	1	'T'	1	0	1	1	1
0	1	4	1	2	'T'	1	4	1	2	5
1	1	1	0	2	'T'	0	0	-1	1	1
0	0	4	0	2	'T'	0	4	0	2	4
0	1	0	1	0	'T'	1	0	1	0	1
0	1	2	1	0	'T'	1	2	1	0	3
0	1	0	0	2	'T'	1	0	0	2	1
0	0	0	NA	NA	'T'	0	0	NA	NA	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	1	0	2	'T'	0	0	-1	1	1
1	1	0	1	0.5	'T'	0	-1	0	-0.5	0
0	1	0	1	2	'T'	1	0	1	2	1
0	0	2	1	0	'T'	0	2	1	0	2
1	1	2	1	2	'T'	0	1	0	1	2
1	1	1	0	0	'T'	0	0	-1	-1	1
0	0	2	NA	NA	'T'	0	2	NA	NA	2
1	0	0	NA	NA	'T'	-1	-1	NA	NA	-1
1	1	3	1	2	'T'	0	2	0	1	3
1	0	0	1	0	'T'	-1	-1	0	-1	-1
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
0	0	0	NA	NA	'T'	0	0	NA	NA	0
0	0	1	0	2	'T'	0	1	0	2	1
1	1	0	1	1	'T'	0	-1	0	0	0
1	0	0	0	0.5	'T'	-1	-1	-1	-0.5	-1
1	1	4	0	2	'T'	0	3	-1	1	4
0	0	0	1	0.5	'T'	0	0	1	0.5	0
0	0	1	NA	NA	'T'	0	1	NA	NA	1
0	0	0	1	0.5	'T'	0	0	1	0.5	0
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
1	1	4	0	2	'T'	0	3	-1	1	4
0	1	1	1	0	'E'	1	1	1	0	2
0	1	0	1	1	'E'	1	0	1	1	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	0	0	'E'	0	-1	-1	-1	0
1	1	0	1	0.5	'E'	0	-1	0	-0.5	0
0	0	0	1	0	'E'	0	0	1	0	0
0	1	4	1	2	'E'	1	4	1	2	5
0	1	0	0	0	'E'	1	0	0	0	1
1	1	0	0	1	'E'	0	-1	-1	0	0
1	1	4	1	2	'E'	0	3	0	1	4
0	0	4	0	0.5	'E'	0	4	0	0.5	4
0	1	0	1	2	'E'	1	0	1	2	1
1	1	1	1	2	'E'	0	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	4	NA	NA	'E'	0	4	NA	NA	4
0	1	0	0	0	'E'	1	0	0	0	1
0	1	2	1	0	'E'	1	2	1	0	3
0	1	0	1	0.5	'E'	1	0	1	0.5	1
0	1	4	NA	NA	'E'	1	4	NA	NA	5
0	0	4	0	2	'E'	0	4	0	2	4
0	0	0	NA	NA	'E'	0	0	NA	NA	0
0	1	0	1	0	'E'	1	0	1	0	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	0	0	1	0	'E'	-1	-1	0	-1	-1
0	0	2	1	2	'E'	0	2	1	2	2
0	1	0	0	1	'E'	1	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	0	0	0	'E'	0	0	0	0	0
1	1	4	1	1	'E'	0	3	0	0	4
1	1	4	1	2	'E'	0	3	0	1	4
0	1	2	0	0	'S'	1	2	0	0	3
0	1	0	0	0	'S'	1	0	0	0	1
0	1	0	0	0	'S'	1	0	0	0	1
0	1	4	0	0	'S'	1	4	0	0	5
1	1	0	1	2	'S'	0	-1	0	1	0
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	1	1	2	'S'	0	1	1	2	1
1	1	2	1	2	'S'	0	1	0	1	2
1	0	0	1	2	'S'	-1	-1	0	1	-1
1	1	2	1	2	'S'	0	1	0	1	2
0	0	0	1	2	'S'	0	0	1	2	0
0	0	4	1	2	'S'	0	4	1	2	4
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	NA	NA	'S'	-1	-1	NA	NA	-1
1	1	4	1	2	'S'	0	3	0	1	4
0	0	2	1	2	'S'	0	2	1	2	2
0	0	2	NA	NA	'S'	0	2	NA	NA	2
1	1	0	0	0	'S'	0	-1	-1	-1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	NA	NA	'S'	0	3	NA	NA	4
0	1	0	1	2	'S'	1	0	1	2	1
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	1	2	'S'	0	3	0	1	4
1	1	4	1	2	'S'	0	3	0	1	4
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	0	0	0	'S'	0	0	0	0	0
1	1	2	0	0	'S'	0	1	-1	-1	2
0	0	1	1	2	'S'	0	1	1	2	1
0	0	0	0	0	'S'	0	0	0	0	0
0	0	2	1	2	'S'	0	2	1	2	2
0	1	1	0	0	'S'	1	1	0	0	2

 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 '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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140356&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140356&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140356&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 'George Udny Yule' @ yule.wessa.net

 ANOVA Model post1-pre ~ Treatment means 0.364 -0.306 -0.256

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post1-pre  ~  Treatment \tabularnewline
means & 0.364 & -0.306 & -0.256 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140356&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post1-pre  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]0.364[/C][C]-0.306[/C][C]-0.256[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140356&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140356&T=1

As an alternative you can also use a QR Code:

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

 ANOVA Model post1-pre ~ Treatment means 0.364 -0.306 -0.256

 ANOVA Statistics Df Sum Sq Mean Sq F value Pr(>F) Treatment 2 1.825 0.912 3.199 0.045 Residuals 102 29.09 0.285

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
& Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 2 & 1.825 & 0.912 & 3.199 & 0.045 \tabularnewline
Residuals & 102 & 29.09 & 0.285 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140356&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Treatment[/C][C]2[/C][C]1.825[/C][C]0.912[/C][C]3.199[/C][C]0.045[/C][/ROW]
[ROW][C]Residuals[/C][C]102[/C][C]29.09[/C][C]0.285[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140356&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140356&T=2

As an alternative you can also use a QR Code:

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

 ANOVA Statistics Df Sum Sq Mean Sq F value Pr(>F) Treatment 2 1.825 0.912 3.199 0.045 Residuals 102 29.09 0.285

 Tukey Honest Significant Difference Comparisons diff lwr upr p adj S-E -0.306 -0.615 0.002 0.052 T-E -0.256 -0.56 0.049 0.118 T-S 0.051 -0.249 0.35 0.914

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
& diff & lwr & upr & p adj \tabularnewline
S-E & -0.306 & -0.615 & 0.002 & 0.052 \tabularnewline
T-E & -0.256 & -0.56 & 0.049 & 0.118 \tabularnewline
T-S & 0.051 & -0.249 & 0.35 & 0.914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140356&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C]S-E[/C][C]-0.306[/C][C]-0.615[/C][C]0.002[/C][C]0.052[/C][/ROW]
[ROW][C]T-E[/C][C]-0.256[/C][C]-0.56[/C][C]0.049[/C][C]0.118[/C][/ROW]
[ROW][C]T-S[/C][C]0.051[/C][C]-0.249[/C][C]0.35[/C][C]0.914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140356&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140356&T=3

As an alternative you can also use a QR Code:

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

 Tukey Honest Significant Difference Comparisons diff lwr upr p adj S-E -0.306 -0.615 0.002 0.052 T-E -0.256 -0.56 0.049 0.118 T-S 0.051 -0.249 0.35 0.914

 Levenes Test for Homogeneity of Variance Df F value Pr(>F) Group 2 1.11 0.334 102

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
& Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.11 & 0.334 \tabularnewline
& 102 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140356&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]2[/C][C]1.11[/C][C]0.334[/C][/ROW]
[ROW][C] [/C][C]102[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140356&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140356&T=4

As an alternative you can also use a QR Code:

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

 Levenes Test for Homogeneity of Variance Df F value Pr(>F) Group 2 1.11 0.334 102

Parameters (Session):
par1 = 7 ; par2 = 6 ; par3 = TRUE ;
Parameters (R input):
par1 = 7 ; par2 = 6 ; par3 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){ a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE) a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residuals',,TRUE) a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-levene.test(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')