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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 computationTue, 21 Oct 2014 20:42:53 +0100
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/Oct/21/t1413920607mfa46i8wrhmqll1.htm/, Retrieved Wed, 11 Feb 2026 15:13:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=244727, Retrieved Wed, 11 Feb 2026 15:13:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact351

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)] [Q6_WS5_2] [2014-10-21 19:42:53] [e89b1602ca7c278e2fffead05eac818b] [Current]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Q7_WS5] [2014-10-21 19:55:47] [189b7d469e4e3b4e868a6af83e3b3816]
-    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Q7_WS5_CORRECT] [2014-10-21 19:58:09] [189b7d469e4e3b4e868a6af83e3b3816]
- RM D      [Two-Way ANOVA] [Q8_WS5] [2014-10-21 20:07:20] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2015-01-19 19:52:29] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Testing Mean with unknown Variance - Critical Value] [] [2015-01-19 21:02:02] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Skewness and Kurtosis Test] [] [2015-01-19 21:05:07] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Central Tendency] [] [2015-01-19 21:06:37] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Two-Way ANOVA] [] [2015-01-19 21:08:51] [189b7d469e4e3b4e868a6af83e3b3816]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2015-01-19 21:11:23] [189b7d469e4e3b4e868a6af83e3b3816]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244727&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244727&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
Exp1_post3-pre ~ Exp1_Treat
means0.3-0.067-0.267

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Exp1_post3-pre  ~  Exp1_Treat \tabularnewline
means & 0.3 & -0.067 & -0.267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244727&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Exp1_post3-pre  ~  Exp1_Treat[/C][/ROW]
[ROW][C]means[/C][C]0.3[/C][C]-0.067[/C][C]-0.267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244727&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
Exp1_post3-pre ~ Exp1_Treat
means0.3-0.067-0.267






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Exp1_Treat21.1560.5781.3720.259
Residuals8736.6330.421 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Exp1_Treat & 2 & 1.156 & 0.578 & 1.372 & 0.259 \tabularnewline
Residuals & 87 & 36.633 & 0.421 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244727&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]Exp1_Treat[/C][C]2[/C][C]1.156[/C][C]0.578[/C][C]1.372[/C][C]0.259[/C][/ROW]
[ROW][C]Residuals[/C][C]87[/C][C]36.633[/C][C]0.421[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244727&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244727&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)
Exp1_Treat21.1560.5781.3720.259
Residuals8736.6330.421






Tukey Honest Significant Difference Comparisons
difflwruprp adj
'S'-'E'-0.067-0.4660.3330.917
'T'-'E'-0.267-0.6660.1330.255
'T'-'S'-0.2-0.60.20.46

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
'S'-'E' & -0.067 & -0.466 & 0.333 & 0.917 \tabularnewline
'T'-'E' & -0.267 & -0.666 & 0.133 & 0.255 \tabularnewline
'T'-'S' & -0.2 & -0.6 & 0.2 & 0.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244727&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]-0.067[/C][C]-0.466[/C][C]0.333[/C][C]0.917[/C][/ROW]
[ROW][C]'T'-'E'[/C][C]-0.267[/C][C]-0.666[/C][C]0.133[/C][C]0.255[/C][/ROW]
[ROW][C]'T'-'S'[/C][C]-0.2[/C][C]-0.6[/C][C]0.2[/C][C]0.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244727&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244727&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'-'E'-0.067-0.4660.3330.917
'T'-'E'-0.267-0.6660.1330.255
'T'-'S'-0.2-0.60.20.46






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group21.2470.292
87 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.247 & 0.292 \tabularnewline
  & 87 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244727&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]1.247[/C][C]0.292[/C][/ROW]
[ROW][C] [/C][C]87[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244727&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244727&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)
Group21.2470.292
87


Figures (Output of Computation)

Input Parameters & R Code

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