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Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 27 Oct 2011 15:13:12 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/27/t1319742832l8nqh0znmztihyx.htm/, Retrieved Thu, 31 Oct 2024 23:29:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=137495, Retrieved Thu, 31 Oct 2024 23:29:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-10-27 19:13:12] [694c30abd2a3b2ee5cb46fc74cb5bfb9] [Current]
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Dataseries X:
1	2	0	0
1	0	0	0
1	0	0	0
1	4	0	0
0	-1	0	1
-1	-1	0	1
0	1	1	2
0	1	0	1
-1	-1	0	1
0	1	0	1
0	0	1	2
0	4	1	2
0	4	1	2
-1	-1	0	1
0	0	NA	NA
0	4	1	2
-1	-1	NA	NA
0	3	0	1
0	2	1	2
0	2	NA	NA
0	-1	-1	-1
0	-1	0	1
0	3	NA	NA
1	0	1	2
0	-1	0	1
0	-1	0	1
0	3	0	1
0	3	0	1
0	0	NA	NA
0	0	0	0
0	1	-1	-1
0	1	1	2
0	0	0	0
0	2	1	2
1	1	0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137495&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137495&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137495&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







ANOVA Model
post2-pre ~ post4-pre
means010.33320.8

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post2-pre  ~  post4-pre \tabularnewline
means & 0 & 1 & 0.333 & 2 & 0.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137495&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post2-pre  ~  post4-pre[/C][/ROW]
[ROW][C]means[/C][C]0[/C][C]1[/C][C]0.333[/C][C]2[/C][C]0.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137495&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137495&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 ~ post4-pre
means010.33320.8







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
post4-pre416.4194.1051.4750.234
Residuals3083.4672.782

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post4-pre & 4 & 16.419 & 4.105 & 1.475 & 0.234 \tabularnewline
Residuals & 30 & 83.467 & 2.782 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137495&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]post4-pre[/C][C]4[/C][C]16.419[/C][C]4.105[/C][C]1.475[/C][C]0.234[/C][/ROW]
[ROW][C]Residuals[/C][C]30[/C][C]83.467[/C][C]2.782[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137495&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137495&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)
post4-pre416.4194.1051.4750.234
Residuals3083.4672.782







Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--11-2.8794.8790.943
1--10.333-3.3624.0290.999
2--12-1.7825.7820.55
NA--10.8-3.2484.8480.978
1-0-0.667-2.9681.6340.916
2-01-1.4383.4380.757
NA-0-0.2-3.0332.6331
2-11.667-0.4673.80.184
NA-10.467-2.1093.0420.984
NA-2-1.2-3.8991.4990.699

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & 1 & -2.879 & 4.879 & 0.943 \tabularnewline
1--1 & 0.333 & -3.362 & 4.029 & 0.999 \tabularnewline
2--1 & 2 & -1.782 & 5.782 & 0.55 \tabularnewline
NA--1 & 0.8 & -3.248 & 4.848 & 0.978 \tabularnewline
1-0 & -0.667 & -2.968 & 1.634 & 0.916 \tabularnewline
2-0 & 1 & -1.438 & 3.438 & 0.757 \tabularnewline
NA-0 & -0.2 & -3.033 & 2.633 & 1 \tabularnewline
2-1 & 1.667 & -0.467 & 3.8 & 0.184 \tabularnewline
NA-1 & 0.467 & -2.109 & 3.042 & 0.984 \tabularnewline
NA-2 & -1.2 & -3.899 & 1.499 & 0.699 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137495&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]0--1[/C][C]1[/C][C]-2.879[/C][C]4.879[/C][C]0.943[/C][/ROW]
[ROW][C]1--1[/C][C]0.333[/C][C]-3.362[/C][C]4.029[/C][C]0.999[/C][/ROW]
[ROW][C]2--1[/C][C]2[/C][C]-1.782[/C][C]5.782[/C][C]0.55[/C][/ROW]
[ROW][C]NA--1[/C][C]0.8[/C][C]-3.248[/C][C]4.848[/C][C]0.978[/C][/ROW]
[ROW][C]1-0[/C][C]-0.667[/C][C]-2.968[/C][C]1.634[/C][C]0.916[/C][/ROW]
[ROW][C]2-0[/C][C]1[/C][C]-1.438[/C][C]3.438[/C][C]0.757[/C][/ROW]
[ROW][C]NA-0[/C][C]-0.2[/C][C]-3.033[/C][C]2.633[/C][C]1[/C][/ROW]
[ROW][C]2-1[/C][C]1.667[/C][C]-0.467[/C][C]3.8[/C][C]0.184[/C][/ROW]
[ROW][C]NA-1[/C][C]0.467[/C][C]-2.109[/C][C]3.042[/C][C]0.984[/C][/ROW]
[ROW][C]NA-2[/C][C]-1.2[/C][C]-3.899[/C][C]1.499[/C][C]0.699[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137495&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137495&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
0--11-2.8794.8790.943
1--10.333-3.3624.0290.999
2--12-1.7825.7820.55
NA--10.8-3.2484.8480.978
1-0-0.667-2.9681.6340.916
2-01-1.4383.4380.757
NA-0-0.2-3.0332.6331
2-11.667-0.4673.80.184
NA-10.467-2.1093.0420.984
NA-2-1.2-3.8991.4990.699







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group40.0860.986
30

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 0.086 & 0.986 \tabularnewline
  & 30 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137495&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]4[/C][C]0.086[/C][C]0.986[/C][/ROW]
[ROW][C] [/C][C]30[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137495&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137495&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)
Group40.0860.986
30



Parameters (Session):
par1 = 2 ; par2 = 4 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 4 ; 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){
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<-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')