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Author's title

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 computationTue, 02 Nov 2010 19:07:10 +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/2010/Nov/02/t12887247558jejaic6t44bqzr.htm/, Retrieved Sun, 28 Apr 2024 02:27:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91986, Retrieved Sun, 28 Apr 2024 02:27:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
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)] [WS5 vraag 6 korte...] [2010-10-31 10:26:42] [65eb19f81eab2b6e672eafaed2a27190]
- R PD  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5/1 q6 kt] [2010-11-02 18:59:43] [04d4386fa51dbd2ef12d0f1f80644886]
-    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5/1 q6 lt] [2010-11-02 19:07:10] [de8ccb310fbbdc3d90ae577a3e011cf9] [Current]
-    D        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5/1 q7 kt] [2010-11-02 19:24:09] [04d4386fa51dbd2ef12d0f1f80644886]
-    D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5/1 q7 lt] [2010-11-02 19:29:11] [04d4386fa51dbd2ef12d0f1f80644886]
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Dataseries X:
'T'	1
'T'	-3
'T'	2.5
'T'	0
'T'	-2
'T'	-3
'T'	-3
'T'	-1
'T'	2
'T'	-2
'T'	2
'T'	0
'T'	2
'T'	-2
'T'	NA
'T'	-3
'T'	-2
'T'	-1.5
'T'	-2
'T'	2
'T'	-1
'T'	0
'T'	NA
'T'	NA
'T'	0
'T'	-1
'T'	NA
'T'	NA
'T'	-1
'T'	-2
'T'	-1.5
'T'	1
'T'	-0.5
'T'	NA
'T'	-0.5
'T'	NA
'T'	1
'E'	1
'E'	-1
'E'	1
'E'	-2
'E'	1
'E'	-1
'E'	-1.5
'E'	0
'E'	2
'E'	0
'E'	-2
'E'	1
'E'	3.5
'E'	-2
'E'	-2
'E'	-2
'E'	NA
'E'	0
'E'	2
'E'	-0.5
'E'	NA
'E'	2
'E'	NA
'E'	0
'E'	1
'E'	-2
'E'	-1
'E'	0
'E'	-1
'E'	-2
'E'	0
'E'	2
'E'	1
'S'	2
'S'	0
'S'	0
'S'	4
'S'	-3
'S'	-3
'S'	-1
'S'	-1
'S'	-3
'S'	-1
'S'	-2
'S'	2
'S'	2
'S'	-3
'S'	NA
'S'	2
'S'	NA
'S'	1
'S'	0
'S'	NA
'S'	-1
'S'	-3
'S'	NA
'S'	-2
'S'	-3
'S'	-3
'S'	1
'S'	1
'S'	NA
'S'	0
'S'	1
'S'	-1
'S'	0
'S'	0
'S'	1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91986&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91986&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'George Udny Yule' @ 72.249.76.132







ANOVA Model
post3-pre ~ Treatment
means-0.083-0.35-0.533

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post3-pre  ~  Treatment \tabularnewline
means & -0.083 & -0.35 & -0.533 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91986&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post3-pre  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]-0.083[/C][C]-0.35[/C][C]-0.533[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91986&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
post3-pre ~ Treatment
means-0.083-0.35-0.533







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment24.4062.2030.7410.48
Residuals87258.752.974

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 2 & 4.406 & 2.203 & 0.741 & 0.48 \tabularnewline
Residuals & 87 & 258.75 & 2.974 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91986&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]Treatment[/C][C]2[/C][C]4.406[/C][C]2.203[/C][C]0.741[/C][C]0.48[/C][/ROW]
[ROW][C]Residuals[/C][C]87[/C][C]258.75[/C][C]2.974[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91986&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91986&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)
Treatment24.4062.2030.7410.48
Residuals87258.752.974







Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-E-0.35-1.4120.7120.713
T-E-0.533-1.5950.5280.458
T-S-0.183-1.2450.8780.911

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-E & -0.35 & -1.412 & 0.712 & 0.713 \tabularnewline
T-E & -0.533 & -1.595 & 0.528 & 0.458 \tabularnewline
T-S & -0.183 & -1.245 & 0.878 & 0.911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91986&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]S-E[/C][C]-0.35[/C][C]-1.412[/C][C]0.712[/C][C]0.713[/C][/ROW]
[ROW][C]T-E[/C][C]-0.533[/C][C]-1.595[/C][C]0.528[/C][C]0.458[/C][/ROW]
[ROW][C]T-S[/C][C]-0.183[/C][C]-1.245[/C][C]0.878[/C][C]0.911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91986&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91986&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
S-E-0.35-1.4120.7120.713
T-E-0.533-1.5950.5280.458
T-S-0.183-1.2450.8780.911







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.7240.488
87

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.724 & 0.488 \tabularnewline
  & 87 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91986&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]0.724[/C][C]0.488[/C][/ROW]
[ROW][C] [/C][C]87[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91986&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91986&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)
Group20.7240.488
87



Parameters (Session):
Parameters (R input):
par1 = 2 ; 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){
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')