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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationWed, 17 Dec 2014 13:53:10 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t1418824399xf2gsiukonaowk6.htm/, Retrieved Thu, 16 May 2024 18:43:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270271, Retrieved Thu, 16 May 2024 18:43:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [] [2014-12-17 12:13:13] [93cb0d178904cf975da218b7c929e42d]
- R P     [Two-Way ANOVA] [] [2014-12-17 13:53:10] [3bf75e933754a2000011d1e8d1f109e9] [Current]
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Dataseries X:
1 50 0
1 54 0
1 71 1
1 54 1
1 65 1
1 73 0
1 52 1
1 84 1
1 42 1
1 66 1
1 65 1
1 73 0
1 75 0
0 72 0
1 66 1
1 70 0
1 81 0
1 69 1
1 71 0
1 68 1
1 70 1
0 68 1
1 67 1
1 76 0
1 70 0
1 60 0
1 72 1
1 71 1
1 70 0
0 64 1
1 76 0
1 68 1
1 76 1
0 65 1
1 67 0
0 75 1
1 60 1
0 73 1
1 63 1
1 70 1
1 66 1
1 64 1
1 70 0
1 75 0
1 60 0
1 66 1
1 59 0
1 78 0
1 67 0
0 59 1
1 66 0
1 71 1
0 66 0
0 72 0
0 71 1
0 59 0
0 78 0
0 65 1
0 65 0
0 71 0
0 72 1
0 66 0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270271&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270271&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270271&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means68.625-0.006-0.625-1.911

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 68.625 & -0.006 & -0.625 & -1.911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270271&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]68.625[/C][C]-0.006[/C][C]-0.625[/C][C]-1.911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270271&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270271&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
means68.625-0.006-0.625-1.911







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A113.02513.0250.2290.634
Treatment_B162.44962.4491.0980.299
Treatment_A:Treatment_B111.2211.220.1970.659
Residuals583298.66156.873

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 13.025 & 13.025 & 0.229 & 0.634 \tabularnewline
Treatment_B & 1 & 62.449 & 62.449 & 1.098 & 0.299 \tabularnewline
Treatment_A:Treatment_B & 1 & 11.22 & 11.22 & 0.197 & 0.659 \tabularnewline
Residuals & 58 & 3298.661 & 56.873 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270271&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]13.025[/C][C]13.025[/C][C]0.229[/C][C]0.634[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]62.449[/C][C]62.449[/C][C]1.098[/C][C]0.299[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]11.22[/C][C]11.22[/C][C]0.197[/C][C]0.659[/C][/ROW]
[ROW][C]Residuals[/C][C]58[/C][C]3298.661[/C][C]56.873[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270271&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270271&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_A113.02513.0250.2290.634
Treatment_B162.44962.4491.0980.299
Treatment_A:Treatment_B111.2211.220.1970.659
Residuals583298.66156.873







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-1.027-5.3253.270.634
1-0-2.011-5.8541.8310.299
1:0-0:0-0.006-8.2948.2821
0:1-0:0-0.625-10.3189.0680.998
1:1-0:0-2.542-10.6855.6020.842
0:1-1:0-0.619-8.5677.3280.997
1:1-1:0-2.536-8.4963.4250.676
1:1-0:1-1.917-9.7145.880.915

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -1.027 & -5.325 & 3.27 & 0.634 \tabularnewline
1-0 & -2.011 & -5.854 & 1.831 & 0.299 \tabularnewline
1:0-0:0 & -0.006 & -8.294 & 8.282 & 1 \tabularnewline
0:1-0:0 & -0.625 & -10.318 & 9.068 & 0.998 \tabularnewline
1:1-0:0 & -2.542 & -10.685 & 5.602 & 0.842 \tabularnewline
0:1-1:0 & -0.619 & -8.567 & 7.328 & 0.997 \tabularnewline
1:1-1:0 & -2.536 & -8.496 & 3.425 & 0.676 \tabularnewline
1:1-0:1 & -1.917 & -9.714 & 5.88 & 0.915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270271&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]-1.027[/C][C]-5.325[/C][C]3.27[/C][C]0.634[/C][/ROW]
[ROW][C]1-0[/C][C]-2.011[/C][C]-5.854[/C][C]1.831[/C][C]0.299[/C][/ROW]
[ROW][C]1:0-0:0[/C][C]-0.006[/C][C]-8.294[/C][C]8.282[/C][C]1[/C][/ROW]
[ROW][C]0:1-0:0[/C][C]-0.625[/C][C]-10.318[/C][C]9.068[/C][C]0.998[/C][/ROW]
[ROW][C]1:1-0:0[/C][C]-2.542[/C][C]-10.685[/C][C]5.602[/C][C]0.842[/C][/ROW]
[ROW][C]0:1-1:0[/C][C]-0.619[/C][C]-8.567[/C][C]7.328[/C][C]0.997[/C][/ROW]
[ROW][C]1:1-1:0[/C][C]-2.536[/C][C]-8.496[/C][C]3.425[/C][C]0.676[/C][/ROW]
[ROW][C]1:1-0:1[/C][C]-1.917[/C][C]-9.714[/C][C]5.88[/C][C]0.915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270271&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270271&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
1-0-1.027-5.3253.270.634
1-0-2.011-5.8541.8310.299
1:0-0:0-0.006-8.2948.2821
0:1-0:0-0.625-10.3189.0680.998
1:1-0:0-2.542-10.6855.6020.842
0:1-1:0-0.619-8.5677.3280.997
1:1-1:0-2.536-8.4963.4250.676
1:1-0:1-1.917-9.7145.880.915







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.2810.839
58

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.281 & 0.839 \tabularnewline
  & 58 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270271&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]0.281[/C][C]0.839[/C][/ROW]
[ROW][C] [/C][C]58[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270271&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270271&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)
Group30.2810.839
58



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