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Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationTue, 28 Jan 2020 10:47:35 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Jan/28/t1580205068o3nvwma6kpag2gu.htm/, Retrieved Wed, 21 Apr 2021 07:36:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319051, Retrieved Wed, 21 Apr 2021 07:36:21 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact38
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [vraag 6] [2020-01-28 09:47:35] [43eb2330ebca6ad52336dea971844457] [Current]
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Dataseries X:
21 "'F'" "'S'"
22 "'M'" "'S'"
17 "'M'" "'S'"
21 "'M'" "'S'"
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23 "'M'" "'S'"
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11 "'F'" "'S'"
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16 "'F'" "'S'"
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13 "'F'" "'S'"
20 "'M'" "'B'"
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15 "'F'" "'S'"
15 "'F'" "'S'"
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16 "'F'" "'B'"
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18 "'F'" "'B'"
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22 "'M'" "'S'"
18 "'F'" "'B'"
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13 "'M'" "'B'"
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18 "'M'" "'B'"
12 "'F'" "'B'"
16 "'F'" "'B'"
21 "'F'" "'S'"
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Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319051&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319051&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319051&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 Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Response ~ Treatment_A * Treatment_B
means17.478-0.401-0.142.124

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 17.478 & -0.401 & -0.14 & 2.124 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319051&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]17.478[/C][C]-0.401[/C][C]-0.14[/C][C]2.124[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319051&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319051&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
Response ~ Treatment_A * Treatment_B
means17.478-0.401-0.142.124







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A156.06956.0698.0960.005
Treatment_B133.43733.4374.8280.029
Treatment_A:Treatment_B140.04240.0425.7820.017
Residuals1751211.8936.925

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 56.069 & 56.069 & 8.096 & 0.005 \tabularnewline
Treatment_B & 1 & 33.437 & 33.437 & 4.828 & 0.029 \tabularnewline
Treatment_A:Treatment_B & 1 & 40.042 & 40.042 & 5.782 & 0.017 \tabularnewline
Residuals & 175 & 1211.893 & 6.925 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319051&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][/C][C]1[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]1[/C][C]56.069[/C][C]56.069[/C][C]8.096[/C][C]0.005[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]33.437[/C][C]33.437[/C][C]4.828[/C][C]0.029[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]40.042[/C][C]40.042[/C][C]5.782[/C][C]0.017[/C][/ROW]
[ROW][C]Residuals[/C][C]175[/C][C]1211.893[/C][C]6.925[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319051&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319051&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
DfSum SqMean SqF valuePr(>F)
1
Treatment_A156.06956.0698.0960.005
Treatment_B133.43733.4374.8280.029
Treatment_A:Treatment_B140.04240.0425.7820.017
Residuals1751211.8936.925







Tukey Honest Significant Difference Comparisons
difflwruprp adj
'M'-'F'1.120.3431.8960.005
'S'-'B'0.9690.0981.840.029
'M':'B'-'F':'B'-0.401-2.3551.5530.951
'F':'S'-'F':'B'-0.14-1.7961.5160.996
'M':'S'-'F':'B'1.583-0.0733.2390.067
'F':'S'-'M':'B'0.262-1.3221.8450.974
'M':'S'-'M':'B'1.9850.4013.5690.007
'M':'S'-'F':'S'1.7230.5262.920.001

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
'M'-'F' & 1.12 & 0.343 & 1.896 & 0.005 \tabularnewline
'S'-'B' & 0.969 & 0.098 & 1.84 & 0.029 \tabularnewline
'M':'B'-'F':'B' & -0.401 & -2.355 & 1.553 & 0.951 \tabularnewline
'F':'S'-'F':'B' & -0.14 & -1.796 & 1.516 & 0.996 \tabularnewline
'M':'S'-'F':'B' & 1.583 & -0.073 & 3.239 & 0.067 \tabularnewline
'F':'S'-'M':'B' & 0.262 & -1.322 & 1.845 & 0.974 \tabularnewline
'M':'S'-'M':'B' & 1.985 & 0.401 & 3.569 & 0.007 \tabularnewline
'M':'S'-'F':'S' & 1.723 & 0.526 & 2.92 & 0.001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319051&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]'M'-'F'[/C][C]1.12[/C][C]0.343[/C][C]1.896[/C][C]0.005[/C][/ROW]
[ROW][C]'S'-'B'[/C][C]0.969[/C][C]0.098[/C][C]1.84[/C][C]0.029[/C][/ROW]
[ROW][C]'M':'B'-'F':'B'[/C][C]-0.401[/C][C]-2.355[/C][C]1.553[/C][C]0.951[/C][/ROW]
[ROW][C]'F':'S'-'F':'B'[/C][C]-0.14[/C][C]-1.796[/C][C]1.516[/C][C]0.996[/C][/ROW]
[ROW][C]'M':'S'-'F':'B'[/C][C]1.583[/C][C]-0.073[/C][C]3.239[/C][C]0.067[/C][/ROW]
[ROW][C]'F':'S'-'M':'B'[/C][C]0.262[/C][C]-1.322[/C][C]1.845[/C][C]0.974[/C][/ROW]
[ROW][C]'M':'S'-'M':'B'[/C][C]1.985[/C][C]0.401[/C][C]3.569[/C][C]0.007[/C][/ROW]
[ROW][C]'M':'S'-'F':'S'[/C][C]1.723[/C][C]0.526[/C][C]2.92[/C][C]0.001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319051&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319051&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
difflwruprp adj
'M'-'F'1.120.3431.8960.005
'S'-'B'0.9690.0981.840.029
'M':'B'-'F':'B'-0.401-2.3551.5530.951
'F':'S'-'F':'B'-0.14-1.7961.5160.996
'M':'S'-'F':'B'1.583-0.0733.2390.067
'F':'S'-'M':'B'0.262-1.3221.8450.974
'M':'S'-'M':'B'1.9850.4013.5690.007
'M':'S'-'F':'S'1.7230.5262.920.001







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.880.453
175

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.88 & 0.453 \tabularnewline
  & 175 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319051&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]3[/C][C]0.88[/C][C]0.453[/C][/ROW]
[ROW][C] [/C][C]175[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319051&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319051&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
DfF valuePr(>F)
Group30.880.453
175



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = 7-point Likert ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
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<-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')