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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 computationMon, 15 Dec 2014 08:16:56 +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/15/t1418632667swimm4mf1pqs3r4.htm/, Retrieved Thu, 16 May 2024 23:19:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267956, Retrieved Thu, 16 May 2024 23:19:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

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)] [anova] [2014-12-15 08:16:56] [0e510e249d31411b3faa1a25774a526d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	12,9
1	12,2
0	12,8
1	7,4
1	6,7
1	12,6
0	14,8
1	13,3
1	11,1
1	8,2
1	11,4
1	6,4
1	10,6
0	12
0	6,3
0	11,3
1	11,9
0	9,3
1	9,6
0	10
1	6,4
1	13,8
0	10,8
1	13,8
1	11,7
1	10,9
1	16,1
0	13,4
1	9,9
0	11,5
0	8,3
0	11,7
1	9
1	9,7
1	10,8
1	10,3
0	10,4
1	12,7
1	9,3
0	11,8
1	5,9
1	11,4
1	13
1	10,8
1	12,3
0	11,3
1	11,8
1	7,9
0	12,7
1	12,3
1	11,6
1	6,7
1	10,9
1	12,1
1	13,3
1	10,1
0	5,7
1	14,3
0	8
1	13,3
1	9,3
0	12,5
0	7,6
1	15,9
0	9,2
1	9,1
0	11,1
1	13
1	14,5
0	12,2
0	12,3
0	11,4
0	8,8
1	14,6
0	12,6
0	13
1	12,6
0	13,2
0	9,9
1	7,7
0	10,5
0	13,4
0	10,9
1	4,3
0	10,3
1	11,8
1	11,2
0	11,4
0	8,6
0	13,2
1	12,6
1	5,6
1	9,9
0	8,8
1	7,7
0	9
1	7,3
1	11,4
1	13,6
1	7,9
1	10,7
0	10,3
1	8,3
1	9,6
1	14,2
0	8,5
0	13,5
0	4,9
0	6,4
0	9,6
0	11,6
1	11,1
1	4,35
1	12,7
1	18,1
1	17,85
0	16,6
1	12,6
1	17,1
0	19,1
1	16,1
0	13,35
0	18,4
1	14,7
1	10,6
1	12,6
1	16,2
1	13,6
1	18,9
1	14,1
1	14,5
0	16,15
1	14,75
1	14,8
1	12,45
1	12,65
1	17,35
1	8,6
0	18,4
1	16,1
1	11,6
1	17,75
1	15,25
1	17,65
0	16,35
0	17,65
1	13,6
0	14,35
0	14,75
1	18,25
0	9,9
1	16
1	18,25
0	16,85
1	14,6
1	13,85
1	18,95
0	15,6
0	14,85
0	11,75
0	18,45
1	15,9
0	17,1
1	16,1
0	19,9
1	10,95
0	18,45
1	15,1
0	15
0	11,35
1	15,95
0	18,1
1	14,6
1	15,4
1	15,4
1	17,6
1	13,35
0	19,1
1	15,35
0	7,6
0	13,4
0	13,9
1	19,1
0	15,25
1	12,9
0	16,1
0	17,35
0	13,15
0	12,15
1	12,6
1	10,35
1	15,4
1	9,6
0	18,2
0	13,6
1	14,85
0	14,75
0	14,1
0	14,9
0	16,25
1	19,25
1	13,6
0	13,6
0	15,65
1	12,75
0	14,6
1	9,85
1	12,65
0	19,2
1	16,6
1	11,2
1	15,25
0	11,9
0	13,2
0	16,35
1	12,4
1	15,85
1	18,15
1	11,15
0	15,65
0	17,75
0	7,65
1	12,35
1	15,6
0	19,3
0	15,2
0	17,1
1	15,6
1	18,4
0	19,05
0	18,55
0	19,1
1	13,1
1	12,85
1	9,5
1	4,5
0	11,85
1	13,6
1	11,7
1	12,4
0	13,35
0	11,4
1	14,9
0	19,9
1	11,2
1	14,6
0	17,6
1	14,05
0	16,1
1	13,35
1	11,85
0	11,95
1	14,75
0	15,15
1	13,2
0	16,85
1	7,85
0	7,7
0	12,6
1	7,85
1	10,95
0	12,35
1	9,95
1	14,9
0	16,65
1	13,4
0	13,95
0	15,7
1	16,85
1	10,95
0	15,35
1	12,2
0	15,1
0	17,75
1	15,2
0	14,6
0	16,65
1	8,1

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=267956&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=267956&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267956&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
TOT ~ Gender
means13.486-0.899

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
TOT  ~  Gender \tabularnewline
means & 13.486 & -0.899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267956&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]TOT  ~  Gender[/C][/ROW]
[ROW][C]means[/C][C]13.486[/C][C]-0.899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267956&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267956&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
TOT ~ Gender
means13.486-0.899






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Gender155.09755.0974.8480.028
Residuals2763136.40711.364 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Gender & 1 & 55.097 & 55.097 & 4.848 & 0.028 \tabularnewline
Residuals & 276 & 3136.407 & 11.364 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267956&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]Gender[/C][C]1[/C][C]55.097[/C][C]55.097[/C][C]4.848[/C][C]0.028[/C][/ROW]
[ROW][C]Residuals[/C][C]276[/C][C]3136.407[/C][C]11.364[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267956&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267956&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)
Gender155.09755.0974.8480.028
Residuals2763136.40711.364






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-0.899-1.702-0.0950.028

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -0.899 & -1.702 & -0.095 & 0.028 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267956&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]1-0[/C][C]-0.899[/C][C]-1.702[/C][C]-0.095[/C][C]0.028[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267956&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267956&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
1-0-0.899-1.702-0.0950.028






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group11.2610.263
276 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 1.261 & 0.263 \tabularnewline
  & 276 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267956&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]1.261[/C][C]0.263[/C][/ROW]
[ROW][C] [/C][C]276[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267956&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267956&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)
Group11.2610.263
276


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')