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Description of Statistical Computation

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 computationSun, 07 Dec 2014 13:08:43 +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/07/t1417957733p8cvn1i8xg1fekj.htm/, Retrieved Sat, 26 Apr 2025 09:14:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263769, Retrieved Sat, 26 Apr 2025 09:14:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

Tree of Dependent Computations

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)] [] [2014-12-07 12:05:48] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 12:31:37] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 12:52:27] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 13:04:05] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 13:08:43] [1d338d9433eb3ecdb4d9d35f41140a45] [Current]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 13:16:58] [8d160a85bfd9526a7d0e42afc5fb569b]
-   PD              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-07 13:26:34] [8d160a85bfd9526a7d0e42afc5fb569b]
- RM D                [Two-Way ANOVA] [] [2014-12-07 15:34:35] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D                  [Two-Way ANOVA] [] [2014-12-07 16:22:10] [8d160a85bfd9526a7d0e42afc5fb569b]
-    D                    [Two-Way ANOVA] [] [2014-12-07 17:48:21] [8d160a85bfd9526a7d0e42afc5fb569b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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'S' 20
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'B' 27
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'S' 20
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'S' 28
'S' 19
'B' 21
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'S' 18
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'B' 21
'S' 21
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'B' 20
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'B' 27
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'S' 25
'B' 28
'S' 25
'B' 24
'B' 27
'S' 19
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'B' 28
'B' 23
'B' 19
'B' 23
'B' 18
'B' 21
'S' 28
'S' 22
'B' 28
'S' 20
'B' 23
'S' 25
'S' 23
'B' 18
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'S' 19
'S' 20
'S' 27
'B' 27
'B' 20
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'B' 25
'B' 23
'B' 24
'B' 27
'B' 28
'S' 26
'B' 27
'S' 23
'S' 28
'B' 22
'S' 23
'S' 27
'S' 18
'B' 22
'B' 23
'B' 25
'B' 14
'S' 21
'S' 26
'S' 28
'B' 22
'B' 24
'B' 28
'B' 24
'B' 26
'S' 18
'S' 19
'S' 26
'B' 26
'B' 12
'B' 24
'B' 26
'S' 23

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263769&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263769&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263769&T=0

As an alternative you can also use a QR Code:  
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'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
AMS.E3 ~ course_L
means22.905-0.537

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
AMS.E3  ~  course_L \tabularnewline
means & 22.905 & -0.537 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263769&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]AMS.E3  ~  course_L[/C][/ROW]
[ROW][C]means[/C][C]22.905[/C][C]-0.537[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263769&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263769&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Model
AMS.E3 ~ course_L
means22.905-0.537






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
course_L134.89334.8932.9090.089
Residuals4865828.90811.994 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
course_L & 1 & 34.893 & 34.893 & 2.909 & 0.089 \tabularnewline
Residuals & 486 & 5828.908 & 11.994 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263769&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]course_L[/C][C]1[/C][C]34.893[/C][C]34.893[/C][C]2.909[/C][C]0.089[/C][/ROW]
[ROW][C]Residuals[/C][C]486[/C][C]5828.908[/C][C]11.994[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263769&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263769&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
course_L134.89334.8932.9090.089
Residuals4865828.90811.994






Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-B-0.537-1.1560.0820.089

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-B & -0.537 & -1.156 & 0.082 & 0.089 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263769&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-B[/C][C]-0.537[/C][C]-1.156[/C][C]0.082[/C][C]0.089[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263769&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263769&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-B-0.537-1.1560.0820.089






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group13.1440.077
486 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 3.144 & 0.077 \tabularnewline
  & 486 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263769&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]1[/C][C]3.144[/C][C]0.077[/C][/ROW]
[ROW][C] [/C][C]486[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263769&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263769&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group13.1440.077
486


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
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){
'Tukey Plot'
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<-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')