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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 computationFri, 18 Dec 2015 20:09:08 +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/2015/Dec/18/t1450469881dgfq6laih0hrgrr.htm/, Retrieved Thu, 16 May 2024 15:45:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286929, Retrieved Thu, 16 May 2024 15:45:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69

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)] [] [2015-12-18 20:09:08] [07ba906b939ae28b4ecd6e8f542e2409] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6.5 2.3
6.8 1.9
6.8 0.6
6.5 0.6
6.2 -0.4
6.2 -1.1
6.6 -1.7
6.7 -0.8
6.5 -1.2
6.4 -1
6.5 -0.1
6.8 0.3
7.1 0.6
7.2 0.7
7.1 1.7
7 1.8
6.9 2.3
6.9 2.5
7.4 2.6
7.3 2.3
7 2.9
6.8 3
6.5 2.9
6.4 3.1
6.3 3.2
6 3.4
5.9 3.5
5.7 3.4
5.7 3.4
5.7 3.7
6.2 3.8
6.4 3.6
6.2 3.6
6.2 3.6
6.1 3.9
6.1 3.5
6.2 3.7
6.1 3.7
6.1 3.4
6.2 3.2
6.2 2.8
6.2 2.3
6.4 2.3
6.4 2.9
6.4 2.8
6.7 2.8
6.9 2.3
7.1 2.2
7.3 1.5
7.2 1.2
7.1 1.1
6.9 1
6.8 1.2
6.7 1.6
7.2 1.5
7.2 1
7.1 0.9
7.1 0.6
7 0.8
7.1 1
7.3 1.1
7.2 1
7.1 0.9
7 0.6
6.9 0.4
7 0.3
7.5 0.3
7.6 0
7.5 -0.1
7.3 0.1
7.3 -0.1
7.4 -0.4
7.7 -0.7
7.8 -0.4
7.7 -0.4
7.5 0.3
7.3 0.6
7.3 0.6
7.6 0.5
7.6 0.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286929&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286929&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
werkloosheid ~ inflatie
means7.17.2757.76.76.46.26.56.67.67.37.26.97.67.0147.277.2677.17.277.256.77.176.87.16.76.97.46.4336.6336.86.46.255.87566.26766.26.1

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
werkloosheid  ~  inflatie \tabularnewline
means & 7.1 & 7.275 & 7.7 & 6.7 & 6.4 & 6.2 & 6.5 & 6.6 & 7.6 & 7.3 & 7.2 & 6.9 & 7.6 & 7.014 & 7.2 & 7 & 7.267 & 7.1 & 7.2 & 7 & 7.25 & 6.7 & 7.1 & 7 & 6.8 & 7.1 & 6.7 & 6.9 & 7.4 & 6.433 & 6.633 & 6.8 & 6.4 & 6.25 & 5.875 & 6 & 6.267 & 6 & 6.2 & 6.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286929&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]werkloosheid  ~  inflatie[/C][/ROW]
[ROW][C]means[/C][C]7.1[/C][C]7.275[/C][C]7.7[/C][C]6.7[/C][C]6.4[/C][C]6.2[/C][C]6.5[/C][C]6.6[/C][C]7.6[/C][C]7.3[/C][C]7.2[/C][C]6.9[/C][C]7.6[/C][C]7.014[/C][C]7.2[/C][C]7[/C][C]7.267[/C][C]7.1[/C][C]7.2[/C][C]7[/C][C]7.25[/C][C]6.7[/C][C]7.1[/C][C]7[/C][C]6.8[/C][C]7.1[/C][C]6.7[/C][C]6.9[/C][C]7.4[/C][C]6.433[/C][C]6.633[/C][C]6.8[/C][C]6.4[/C][C]6.25[/C][C]5.875[/C][C]6[/C][C]6.267[/C][C]6[/C][C]6.2[/C][C]6.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286929&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
werkloosheid ~ inflatie
means7.17.2757.76.76.46.26.56.67.67.37.26.97.67.0147.277.2677.17.277.256.77.176.87.16.76.97.46.4336.6336.86.46.255.87566.26766.26.1






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
inflatie403713.8892.847764.1350
Residuals404.860.122 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
inflatie & 40 & 3713.88 & 92.847 & 764.135 & 0 \tabularnewline
Residuals & 40 & 4.86 & 0.122 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286929&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]inflatie[/C][C]40[/C][C]3713.88[/C][C]92.847[/C][C]764.135[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]40[/C][C]4.86[/C][C]0.122[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286929&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)
inflatie403713.8892.847764.1350
Residuals404.860.122






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286929&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286929&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286929&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:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group390.640.917
40 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 39 & 0.64 & 0.917 \tabularnewline
  & 40 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286929&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]39[/C][C]0.64[/C][C]0.917[/C][/ROW]
[ROW][C] [/C][C]40[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286929&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286929&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)
Group390.640.917
40


Figures (Output of Computation)

Input Parameters & R Code

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