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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Tue, 30 Oct 2012 18:32:13 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/30/t13516363621e888shlo7x9l46.htm/, Retrieved Tue, 10 Feb 2026 19:43:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185385, Retrieved Tue, 10 Feb 2026 19:43:56 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

414

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2012-10-30 21:05:52] [0f86cfddc502cf698caf54991235c44d]
- R  D  [Paired and Unpaired Two Samples Tests about the Mean] [] [2012-10-30 21:22:01] [0f86cfddc502cf698caf54991235c44d]
-    D    [Paired and Unpaired Two Samples Tests about the Mean] [T-treatment] [2012-10-30 21:40:18] [0f86cfddc502cf698caf54991235c44d]
-    D      [Paired and Unpaired Two Samples Tests about the Mean] [E-treatment] [2012-10-30 21:41:47] [0f86cfddc502cf698caf54991235c44d]
-             [Paired and Unpaired Two Samples Tests about the Mean] [S-treatment] [2012-10-30 21:44:09] [0f86cfddc502cf698caf54991235c44d]
- RMPD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [short term] [2012-10-30 21:59:29] [0f86cfddc502cf698caf54991235c44d]
- R P             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [long term] [2012-10-30 22:05:56] [74be16979710d4c4e7c6647856088456]
- R PD                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [short term] [2012-10-30 22:32:13] [a1c9ee8128156b02a669e54abb47d426] [Current]
- R P                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [long term] [2012-10-30 22:42:38] [0f86cfddc502cf698caf54991235c44d] 
-   P                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [long term] [2012-10-30 22:55:44] [0f86cfddc502cf698caf54991235c44d] 
- R P                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2012-10-30 22:48:22] [0f86cfddc502cf698caf54991235c44d] 
- RM D                    [Two-Way ANOVA] [] [2012-10-30 23:02:36] [0f86cfddc502cf698caf54991235c44d] 
- R P                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [short term] [2012-10-30 22:50:31] [0f86cfddc502cf698caf54991235c44d] 

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Dataseries X:

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Histogram

Boxplots

'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	0	1	1	1	1	2
'WWE'	0	0	0	0	0	0
'WWE'	0	1	1	1	1	2
'WWE'	0	0	1	0	1	1
'WWE'	0	0	0	0	0	0
'WWE'	0	1	1	1	1	2
'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	0	0	NA	0	NA	NA
'WWE'	0	0	1	0	1	1
'WWE'	1	1	NA	0	NA	NA
'WWE'	1	0	0	-1	-1	-1
'WWE'	0	0	0	0	0	0
'WWE'	0	0	1	0	1	1
'WWE'	0	1	0	1	0	1
'WWE'	0	0	0	0	0	0
'WWE'	1	1	0	0	-1	0
'WWE'	0	0	0	0	0	0
'WWE'	0	1	0	1	0	1
'WWE'	0	1	1	1	1	2
'WWE'	0	1	1	1	1	2
'WWE'	0	0	0	0	0	0
'WWE'	1	1	0	0	-1	0
'WWE'	0	1	0	1	0	1
'WWE'	0	1	0	1	0	1
'WWE'	0	0	1	0	1	1
'WWE'	0	1	0	1	0	1
'WWE'	0	1	0	1	0	1
'WWE'	0	0	0	0	0	0
'WWE'	0	0	0	0	0	0
'WWE'	1	1	0	0	-1	0
'WWE'	1	1	0	0	-1	0
'WWE'	0	0	0	0	0	0
'WWE'	0	0	NA	0	NA	NA
'WWE'	0	0	1	0	1	1
'WWE'	0	0	0	0	0	0
'CSWE'	0	0	0	0	0	0
'CSWE'	1	0	NA	-1	NA	NA
'CSWE'	0	0	0	0	0	0
'CSWE'	0	1	NA	1	NA	NA
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	1	0	1	1
'CSWE'	0	0	0	0	0	0
'CSWE'	1	1	0	0	-1	0
'CSWE'	0	0	1	0	1	1
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	0	0	0	0
'CSWE'	0	1	NA	1	NA	NA
'CSWE'	0	1	0	1	0	1
'CSWE'	0	1	NA	1	NA	NA
'CSWE'	1	1	0	0	-1	0
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	NA	0	NA	NA
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	NA	0	NA	NA
'CSWE'	0	0	0	0	0	0
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	1	0	1	1
'CSWE'	0	1	0	1	0	1
'CSWE'	0	1	0	1	0	1
'CSWE'	1	1	0	0	-1	0
'CSWE'	0	0	1	0	1	1
'CSWE'	0	1	1	1	1	2
'CSWE'	0	1	0	1	0	1
'CSWE'	0	0	NA	0	NA	NA
'CSWE'	0	0	0	0	0	0
'CSWE'	0	1	NA	1	NA	NA
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	0	0	0	0
'CSWE'	0	0	0	0	0	0
'CSWE'	0	1	0	1	0	1
'CSWE'	0	1	0	1	0	1
'C'	0	0	0	0	0	0
'C'	0	0	1	0	1	1
'C'	1	0	0	-1	-1	-1
'C'	0	0	1	0	1	1
'C'	0	0	NA	0	NA	NA
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	1	0	1	0	1
'C'	1	1	0	0	-1	0
'C'	0	0	NA	0	NA	NA
'C'	0	0	0	0	0	0
'C'	0	1	0	1	0	1
'C'	0	1	0	1	0	1
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	NA	0	NA	NA
'C'	0	0	0	0	0	0
'C'	0	1	0	1	0	1
'C'	1	1	0	0	-1	0
'C'	0	1	0	1	0	1
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	1	1	0	0	-1	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	1	1	0	0	-1	0
'C'	0	0	1	0	1	1
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	0	0	0	0
'C'	0	0	1	0	1	1
'C'	0	0	0	0	0	0
'C'	0	0	NA	0	NA	NA
'C'	1	1	0	0	-1	0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185385&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185385&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185385&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	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

ANOVA Model
post1 ~ pre
means	0.308	0.505

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post1  ~  pre \tabularnewline
means & 0.308 & 0.505 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185385&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post1  ~  pre[/C][/ROW]
[ROW][C]means[/C][C]0.308[/C][C]0.505[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185385&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185385&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
means	0.308	0.505

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
pre	1	3.534	3.534	16.956	0
Residuals	118	24.591	0.208

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
pre & 1 & 3.534 & 3.534 & 16.956 & 0 \tabularnewline
Residuals & 118 & 24.591 & 0.208 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185385&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]pre[/C][C]1[/C][C]3.534[/C][C]3.534[/C][C]16.956[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]118[/C][C]24.591[/C][C]0.208[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185385&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185385&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)
pre	1	3.534	3.534	16.956	0
Residuals	118	24.591	0.208

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
1-0	0.505	0.262	0.748	0

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.505 & 0.262 & 0.748 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185385&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]1-0[/C][C]0.505[/C][C]0.262[/C][C]0.748[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185385&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185385&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
1-0	0.505	0.262	0.748	0

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	1	0.961	0.329
	118

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.961 & 0.329 \tabularnewline
  & 118 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185385&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]1[/C][C]0.961[/C][C]0.329[/C][/ROW]
[ROW][C] [/C][C]118[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185385&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185385&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	1	0.961	0.329
	118

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 3 ; par2 = 2 ; par3 = TRUE ;

Parameters (R input):

par1 = 3 ; par2 = 2 ; 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) )
load(file='createtable')
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){
'Tukey Plot'
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<-leveneTest(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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code