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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 22:13:22 -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/t1351649628jm87e3tpopvzcou.htm/, Retrieved Fri, 09 May 2025 18:35:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185425, Retrieved Fri, 09 May 2025 18:35:40 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

238

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

-     [Factor Analysis] [Sleep in Mammals ...] [2010-03-21 11:39:53] [b98453cac15ba1066b407e146608df68]
- RMPD  [Testing Mean with unknown Variance - Critical Value] [Hypothesis Test a...] [2010-10-19 11:45:26] [b98453cac15ba1066b407e146608df68]
-   PD    [Testing Mean with unknown Variance - Critical Value] [Vraag 4: Male ] [2010-10-22 09:14:17] [74deae64b71f9d77c839af86f7c687b5]
- RMPD      [Testing Mean with known Variance - Sample Size] [Vraag 9: Minimum ...] [2010-10-22 12:33:36] [74deae64b71f9d77c839af86f7c687b5]
F RMP         [Minimum Sample Size - Testing Mean] [WS4 Q11] [2010-10-24 11:23:12] [afe9379cca749d06b3d6872e02cc47ed]
- R P           [Minimum Sample Size - Testing Mean] [Q11] [2012-10-23 17:08:38] [74be16979710d4c4e7c6647856088456]
- RMPD            [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q1] [2012-10-29 21:27:39] [77d02b0cf2cecd023ffa9a06f056f18d]
- R  D              [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q2] [2012-10-29 21:32:29] [77d02b0cf2cecd023ffa9a06f056f18d]
- RMPD                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q6] [2012-10-29 21:53:23] [77d02b0cf2cecd023ffa9a06f056f18d]
- R P                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q6 - deel 2] [2012-10-29 22:00:33] [77d02b0cf2cecd023ffa9a06f056f18d]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q7 deel 1] [2012-10-29 22:07:14] [77d02b0cf2cecd023ffa9a06f056f18d]
-                           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q7 deel 2] [2012-10-29 22:10:21] [77d02b0cf2cecd023ffa9a06f056f18d]
-   P                           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 7b] [2012-10-31 02:13:22] [bc8de944878a372a2f96eab55bfa1be2] [Current]

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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=185425&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=185425&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185425&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
post2-pre ~ treat
means	-0.057	0.12	0.189

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post2-pre  ~  treat \tabularnewline
means & -0.057 & 0.12 & 0.189 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185425&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post2-pre  ~  treat[/C][/ROW]
[ROW][C]means[/C][C]-0.057[/C][C]0.12[/C][C]0.189[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185425&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185425&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
post2-pre ~ treat
means	-0.057	0.12	0.189

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
treat	2	0.659	0.33	1.047	0.355
Residuals	102	32.103	0.315

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
treat & 2 & 0.659 & 0.33 & 1.047 & 0.355 \tabularnewline
Residuals & 102 & 32.103 & 0.315 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185425&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]treat[/C][C]2[/C][C]0.659[/C][C]0.33[/C][C]1.047[/C][C]0.355[/C][/ROW]
[ROW][C]Residuals[/C][C]102[/C][C]32.103[/C][C]0.315[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185425&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185425&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)
treat	2	0.659	0.33	1.047	0.355
Residuals	102	32.103	0.315

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
CSWE-C	0.12	-0.207	0.446	0.659
WWE-C	0.189	-0.124	0.501	0.326
WWE-CSWE	0.069	-0.251	0.389	0.865

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
CSWE-C & 0.12 & -0.207 & 0.446 & 0.659 \tabularnewline
WWE-C & 0.189 & -0.124 & 0.501 & 0.326 \tabularnewline
WWE-CSWE & 0.069 & -0.251 & 0.389 & 0.865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185425&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]CSWE-C[/C][C]0.12[/C][C]-0.207[/C][C]0.446[/C][C]0.659[/C][/ROW]
[ROW][C]WWE-C[/C][C]0.189[/C][C]-0.124[/C][C]0.501[/C][C]0.326[/C][/ROW]
[ROW][C]WWE-CSWE[/C][C]0.069[/C][C]-0.251[/C][C]0.389[/C][C]0.865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185425&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185425&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
CSWE-C	0.12	-0.207	0.446	0.659
WWE-C	0.189	-0.124	0.501	0.326
WWE-CSWE	0.069	-0.251	0.389	0.865

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	2	0.934	0.396
	102

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.934 & 0.396 \tabularnewline
  & 102 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185425&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]0.934[/C][C]0.396[/C][/ROW]
[ROW][C] [/C][C]102[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185425&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185425&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	0.934	0.396
	102

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0.0 ;

Parameters (R input):

par1 = 6 ; par2 = 1 ; 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