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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_Two Factor ANOVA.wasp

Title produced by software

Two-Way ANOVA

Date of computation

Wed, 20 Jan 2016 14:34:42 +0000

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/2016/Jan/20/t14533005116kuycjuax1lln7c.htm/, Retrieved Tue, 07 May 2024 22:57:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289770, Retrieved Tue, 07 May 2024 22:57:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

113

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

-       [Two-Way ANOVA] [] [2016-01-20 14:34:42] [85e7a66a1e5d24b56c3cf5eab9332807] [Current]

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Dataseries X:

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Histogram

Boxplots

1.8 2.1 1.5
2.1 2 2.1
2.2 2 2.1
2.3 2.1 1.9
2.1 2 1.6
2.7 2.3 2.1
2.1 2.1 2.1
2.4 2.1 2.2
2.9 2.2 1.5
2.2 2.1 1.9
2.1 2.1 2.2
2.2 2.1 1.6
2.2 2 1.5
2.7 2.3 1.9
1.9 1.8 0.1
2 2 2.2
2.5 2.2 1.8
2.2 2 1.6
2.3 2.1 2.2
1.9 2 2.1
2.1 1.8 1.9
3.5 2.2 1.6
2.1 2.2 1.9
2.3 1.7 2.2
2.3 2.1 1.8
2.2 2.3 2.4
3.5 2.7 2.4
1.9 1.9 2.5
1.9 2 1.9
1.9 2 2.1
1.9 1.9 1.9
2.1 2 2.1
2 2 1.5
3.2 2.1 1.9
2.3 2 2.1
2.5 1.8 1.5
1.8 2 2.1
2.4 2.2 2.1
2.8 2.2 1.8
2.3 2.1 2.4
2 1.8 2.1
2.5 1.9 1.9
2.3 2.1 2.1
1.8 2 1.9
1.9 1.9 2.4
2.6 2.2 2.1
2 2 2.2
2.6 2 2.2
1.6 1.7 1.8
2.2 2 2.1
2.1 2.2 2.4
1.8 1.7 2.2
1.8 2 2.1
1.9 2.2 1.5
2.4 2 1.9
1.9 1.9 1.8
2 2 1.8
2.1 2 1.6
1.7 1.6 1.2
1.9 2.1 1.8
2.1 2.1 1.5
2.4 2 2.1
1.8 1.9 2.4
2.3 2.2 2.4
2.1 2.1 1.5
2 1.8 1.8
2.8 2.3 2.1
2 2.3 2.2
2.7 2.2 2.1
2.1 2.1 1.9
2.9 2.2 2.1
2 1.9 1.9
1.8 1.8 1.6
2.6 2.1 2.4
2.1 2 1.9
2.3 2.1 2.1
2.2 2.1 1.8
2 2.1 2.1
2.2 1.8 2.4
2.1 2 2.1
2.1 2.1 2.2
1.9 1.9 2.1
2 2.1 2.2
1.7 1 1.6
2.2 2.2 2.4
2.2 2.1 2.1
2.3 1.9 1.9
2.4 2 2.4
2.1 1.9 2.1
1.9 2 1.8
1.7 1.8 2.1
1.8 2 1.8
1.5 2 1.9
1.9 2 1.9
1.9 1.8 2.4
1.7 2 1.8
1.9 1.1 1.8
1.9 1.8 2.1
1.8 1.8 2.1
2.4 2 2.4
1.8 1.9 1.9
1.9 2.1 1.8
1.8 1.6 1.8
2.1 2.2 2.2
1.9 1.9 2.4
2.2 2 1.8
2 2.1 2.4
1.7 1.3 1.8
1.7 1.8 1.9
1.8 1.9 2.4
1.9 2.1 2.1
1.8 1.8 1.9
1 0.75 2.1
1 1.5 2.7
4 3 2.1
4 2.25 2.1
3 3 2.1
2 1.5 2.1
4 3 2.1
4 3 2.1
4 3 2.1
2 0.75 2.1
4 3 2.4
1 2.25 1.95
3 1.5 2.1
3 1.5 2.1
4 2.25 1.95
3 3 2.1
4 3 2.4
3 1.5 2.1
3 2.25 2.25
4 2.25 2.4
3 1.5 2.25
3 2.25 2.55
2 1.5 1.95
2 2.25 2.4
3 2.25 2.1
1 3 2.1
4 3 2.4
3 3 2.1
2 1.5 2.1
4 3 2.25
4 3 2.25
4 2.25 2.4
4 2.25 2.1
4 2.25 2.4
3 3 2.1
3 2.25 2.1
4 3 2.25
4 3 2.25
4 1.5 2.4
3 2.25 2.25
4 3 2.25
4 2.25 2.1
2 1.5 2.1
2 2.25 2.1
4 2.25 2.7
3 1.5 2.1
3 2.25 2.1
2 1.5 2.25
3 2.25 2.7
2 3 2.4
4 3 2.1
1 3 2.1
4 3 2.4
1 1.5 1.95
4 2.25 2.7
3 1.5 2.1
3 2.25 2.25
2 2.25 2.1
3 2.25 2.7
3 3 2.1
4 1.5 2.1
4 2.25 1.65
4 2.25 1.65
3 3 2.1
3 2.25 2.1
4 3 2.1
4 2.25 2.1
1 1.5 2.1
2 3 2.4
3 1.5 2.4
4 3 2.1
3 3 2.25
4 3 2.4
3 3 2.1
3 2.25 2.1
3 2.25 2.4
3 0.75 2.4
1 3 2.1
1 0.75 2.1
3 1.5 2.4
2 1.5 2.1
3 3 2.7
2 1.5 2.1
2 2.25 2.1
4 3 2.25
2 3 2.1
2 1.5 2.4
3 3 2.25
4 3 2.25
2 1.5 2.1
4 1.5 2.1
3 2.25 2.4
4 1.5 2.25
2 1.5 2.1
1 2.25 2.1
1 1.5 1.65
4 3 2.7
3 3 2.1
1 0.75 1.95
4 1.5 2.25
3 1.5 2.4
2 2.25 1.95
4 2.25 2.1
3 1.5 2.4
3 2.25 2.1
4 2.25 2.4
1 0.75 2.4
3 2.25 2.4
4 3 2.25
1 0.75 2.4
3 0.75 2.1
4 3 2.1
4 3 1.8
1 3 2.7
4 3 2.1
2 1.5 2.1
3 3 2.4
4 3 2.55
4 3 2.55
4 3 2.1
2 1.5 2.1
4 2.25 2.1
2 0.75 2.25
1 0.75 2.25
1 2.25 2.1
4 3 2.1
2 2.25 1.95
2 3 2.4
3 2.25 2.1
2 3 2.4
3 1.5 2.4
4 3 2.4
2 0.75 1.95
3 1.5 2.1
4 3 2.1
3 3 2.55
4 3 2.1
4 2.25 2.1
4 2.25 2.1
2 3 1.95
2 1.5 2.25
2 2.25 2.4
4 2.25 1.95
3 2.25 2.1
2 0.75 2.1
2 2.25 1.95
3 1.5 2.1
3 2.25 2.1
1 1.5 1.95
2 0.75 2.1
2 1.5 1.95
3 1.5 2.4
3 2.25 2.4
2 1.5 2.4
2 1.5 1.95
3 3 2.7
3 2.25 2.1
1 1.5 1.95
3 0.75 2.1
2 2.25 1.95
2 3 2.1
3 3 2.25
3 1.5 2.7
3 1.5 2.1
3 2.25 2.4
1 0.75 1.35

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289770&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]1 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=289770&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289770&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	1 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Parameters (Session):

Parameters (R input):

par1 = ; par2 = ; par3 = ; par4 = FALSE ;

R code (references can be found in the software module):

cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
intercept<-as.logical(par4)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
f2 <- as.character(x[,cat3])
xdf<-data.frame(x1,f1, f2)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, 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$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],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$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
for(i in 1 : length(rownames(anova.xdf))-1){
a<-table.row.start(a)
a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], 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$'Df'[i+1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
dev.off()
bitmap(file='designplot.png')
xdf2 <- xdf # to preserve xdf make copy for function
names(xdf2) <- c(V1, V2, V3)
plot.design(xdf2, main='Design Plot of Group Means')
dev.off()
bitmap(file='interactionplot.png')
interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))
bitmap(file='TukeyHSDPlot.png')
layout(matrix(c(1,2,3,3), 2,2))
plot(thsd, las=1)
dev.off()
}
if(intercept==TRUE){
ntables<-length(names(thsd))
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(nt in 1:ntables){
for(i in 1:length(rownames(thsd[[nt]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
} # end nt
a<-table.end(a)
table.save(a,file='hsdtable.tab')
}#end if hsd tables
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')

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code