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Author*Unverified author*
R Software Module--
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationTue, 08 Nov 2011 14:08:20 -0500
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/Nov/08/t1320779320ri6kn8oap4nlri6.htm/, Retrieved Fri, 29 Mar 2024 02:15:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=140888, Retrieved Fri, 29 Mar 2024 02:15:09 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
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-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Golfballs] [2010-10-25 12:27:51] [b98453cac15ba1066b407e146608df68]
-   PD  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5: Vraag 7] [2010-10-29 09:57:18] [1fd136673b2a4fecb5c545b9b4a05d64]
- RM        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-08 19:08:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
'WWE'	0
'WWE'	0
'WWE'	2
'WWE'	0
'WWE'	2
'WWE'	1
'WWE'	0
'WWE'	2
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	
'WWE'	1
'WWE'	
'WWE'	-1
'WWE'	0
'WWE'	1
'WWE'	1
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	1
'WWE'	2
'WWE'	2
'WWE'	0
'WWE'	0
'WWE'	1
'WWE'	1
'WWE'	1
'WWE'	1
'WWE'	1
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	0
'WWE'	
'WWE'	1
'WWE'	0
'CSWE'	0
'CSWE'	
'CSWE'	0
'CSWE'	
'CSWE'	1
'CSWE'	0
'CSWE'	0
'CSWE'	1
'CSWE'	0
'CSWE'	0
'CSWE'	1
'CSWE'	1
'CSWE'	0
'CSWE'	
'CSWE'	1
'CSWE'	
'CSWE'	0
'CSWE'	1
'CSWE'	
'CSWE'	1
'CSWE'	0
'CSWE'	
'CSWE'	0
'CSWE'	1
'CSWE'	0
'CSWE'	1
'CSWE'	1
'CSWE'	1
'CSWE'	0
'CSWE'	1
'CSWE'	2
'CSWE'	1
'CSWE'	
'CSWE'	0
'CSWE'	
'CSWE'	0
'CSWE'	0
'CSWE'	0
'CSWE'	1
'CSWE'	1
'C'	0
'C'	1
'C'	-1
'C'	1
'C'	
'C'	0
'C'	0
'C'	1
'C'	0
'C'	
'C'	0
'C'	1
'C'	1
'C'	0
'C'	0
'C'	0
'C'	0
'C'	
'C'	0
'C'	1
'C'	0
'C'	1
'C'	0
'C'	0
'C'	0
'C'	0
'C'	0
'C'	0
'C'	0
'C'	0
'C'	0
'C'	1
'C'	0
'C'	0
'C'	0
'C'	1
'C'	0
'C'	
'C'	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140888&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140888&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
Dist ~ Brand
means0.3330.1850.367

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Dist  ~  Brand \tabularnewline
means & 0.333 & 0.185 & 0.367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140888&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Dist  ~  Brand[/C][/ROW]
[ROW][C]means[/C][C]0.333[/C][C]0.185[/C][C]0.367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140888&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
Dist ~ Brand
means0.3330.1850.367







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Brand20.7370.3690.870.426
Residuals4619.5070.424

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Brand & 2 & 0.737 & 0.369 & 0.87 & 0.426 \tabularnewline
Residuals & 46 & 19.507 & 0.424 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140888&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]Brand[/C][C]2[/C][C]0.737[/C][C]0.369[/C][C]0.87[/C][C]0.426[/C][/ROW]
[ROW][C]Residuals[/C][C]46[/C][C]19.507[/C][C]0.424[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140888&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)
Brand20.7370.3690.870.426
Residuals4619.5070.424







Tukey Honest Significant Difference Comparisons
difflwruprp adj
CSWE-C0.185-0.3620.7320.693
WWE-C0.367-0.3091.0420.394
WWE-CSWE0.181-0.4020.7650.733

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
CSWE-C & 0.185 & -0.362 & 0.732 & 0.693 \tabularnewline
WWE-C & 0.367 & -0.309 & 1.042 & 0.394 \tabularnewline
WWE-CSWE & 0.181 & -0.402 & 0.765 & 0.733 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140888&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]CSWE-C[/C][C]0.185[/C][C]-0.362[/C][C]0.732[/C][C]0.693[/C][/ROW]
[ROW][C]WWE-C[/C][C]0.367[/C][C]-0.309[/C][C]1.042[/C][C]0.394[/C][/ROW]
[ROW][C]WWE-CSWE[/C][C]0.181[/C][C]-0.402[/C][C]0.765[/C][C]0.733[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140888&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140888&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
CSWE-C0.185-0.3620.7320.693
WWE-C0.367-0.3091.0420.394
WWE-CSWE0.181-0.4020.7650.733







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.4860.618
46

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.486 & 0.618 \tabularnewline
  & 46 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140888&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]0.486[/C][C]0.618[/C][/ROW]
[ROW][C] [/C][C]46[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140888&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140888&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)
Group20.4860.618
46



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ; par4 = two.sided ; par5 = paired ; par6 = -0.5 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = TRUE ; par4 = two.sided ; par5 = paired ; par6 = -0.5 ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')