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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, 01 Dec 2014 11:25:58 +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/01/t14174331706a4jy14kpxkzqie.htm/, Retrieved Thu, 16 May 2024 21:06:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261733, Retrieved Thu, 16 May 2024 21:06:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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)] [] [2014-10-18 18:42:11] [8f0f7d8870e334acea674e48ede2c797]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-01 11:25:58] [310e7528d8f6aa5642dc98f4186768d1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9 5 4
9 6 6
8 5 5
8 4 6
8 5 5
8 7 4
7 3 0
8 4 5
9 4 3
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3 2 4
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8 2 6
3 0 0
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3 2 1
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0 0 0
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1 0 1
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8 5 5
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NA NA NA
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7 4 6
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NA NA NA
8 7 6
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6 4 5
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8 6 6
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2 3 4
NA NA NA
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8 1 5
6 5 4
4 0 3
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8 5 6
4 3 5
5 7 5
9 6 5
2 2 1
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6 6 6
4 3 4
5 2 3
3 2 5
6 6 5
8 6 5
8 3 5
4 3 4
7 4 5
5 1 6
3 1 4
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5 2 6
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9 5 6
8 1 4
4 4 5
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4 2 2
5 2 2
6 3 5
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3 4 5
8 3 6
6 1 5
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8 1 6
8 9 6
4 3 2
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8 6 6
8 1 4
8 4 6
7 5 6
5 3 3
9 3 6
6 2 4
9 5 6
7 2 5
8 2 4
8 5 6
6 2 5
8 5 6
7 4 2
8 4 6
5 0 3
6 2 6
6 0 4
6 3 5
5 1 3
6 2 6
6 2 4
8 3 4
4 2 3
8 1 3
5 4 3
6 5 5
5 1 5
5 4 5
9 7 4
5 1 2
7 4 6
7 3 4
7 4 4
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6 5 4
7 3 3
4 4 6
7 3 5
4 1 1
7 4 3
3 5 3
5 2 3
7 4 4
8 5 4
9 7 6
9 8 6
6 4 5
7 5 2
2 1 0
5 2 3
6 0 5
7 6 5
6 1 4
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9 4 6
6 2 3
3 4 5
9 3 6
8 2 1
6 1 4
6 3 4
8 6 1
5 2 2
9 8 6
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6 1 5
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6 3 6
7 4 6
4 4 4
7 2 5
4 0 1
6 4 5
8 5 5
'DELETED' "'DELETED'" "'DELETED'"
7 6 3
5 2 3
8 5 6
8 2 5
9 4 6
8 3 5
4 0 0
7 5 6
7 7 5
9 6 5
7 5 5
7 4 5
5 1 2
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7 3 5
5 3 5
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9 3 4
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6 5 3
2 3 2
9 6 6
9 7 5
4 3 3
7 2 5
9 6 5
7 5 4
8 1 6
5 2 3
6 3 3
6 2 4
3 3 4
4 1 3
8 3 6
6 7 5
5 3 4
7 4 4
7 1 5
5 2 6
7 2 5
8 7 4
6 1 5
6 1 3
8 8 5
6 4 5
8 2 5
8 3 5
7 3 4
6 3 5
3 3 6
8 2 5
8 4 5
8 5 6
7 5 4
5 2 4
5 2 3

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261733&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261733&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261733&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'George Udny Yule' @ yule.wessa.net






ANOVA Model
Calculation ~ Algebraic_Reasoning
means3.6155.9418.3336.1956.4196.8457.1257.3727.94487.75

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Calculation  ~  Algebraic_Reasoning \tabularnewline
means & 3.615 & 5.941 & 8.333 & 6.195 & 6.419 & 6.845 & 7.125 & 7.372 & 7.944 & 8 & 7.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261733&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Calculation  ~  Algebraic_Reasoning[/C][/ROW]
[ROW][C]means[/C][C]3.615[/C][C]5.941[/C][C]8.333[/C][C]6.195[/C][C]6.419[/C][C]6.845[/C][C]7.125[/C][C]7.372[/C][C]7.944[/C][C]8[/C][C]7.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261733&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261733&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
Calculation ~ Algebraic_Reasoning
means3.6155.9418.3336.1956.4196.8457.1257.3727.94487.75






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Algebraic_Reasoning1134865.7733169.6161354.7240
Residuals7191682.2272.34 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Algebraic_Reasoning & 11 & 34865.773 & 3169.616 & 1354.724 & 0 \tabularnewline
Residuals & 719 & 1682.227 & 2.34 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261733&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]Algebraic_Reasoning[/C][C]11[/C][C]34865.773[/C][C]3169.616[/C][C]1354.724[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]719[/C][C]1682.227[/C][C]2.34[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261733&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261733&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)
Algebraic_Reasoning1134865.7733169.6161354.7240
Residuals7191682.2272.34






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=261733&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261733&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261733&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)
Group103.790
719 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 10 & 3.79 & 0 \tabularnewline
  & 719 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261733&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]10[/C][C]3.79[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]719[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261733&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261733&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)
Group103.790
719


Figures (Output of Computation)

Input Parameters & R Code

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