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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 computationThu, 07 Nov 2013 06:50:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/07/t13838250694wihiadmtz1ve3w.htm/, Retrieved Fri, 01 Nov 2024 02:24:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223224, Retrieved Fri, 01 Nov 2024 02:24:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

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)] [G2] [2013-11-07 11:50:59] [59964fe9a12819b90671f7c3badeb922] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	88
3	94
3	90
3	73
1	68
2	80
3	86
3	86
2	91
1	79
1	96
3	92
3	72
3	96
1	70
3	86
3	87
3	88
2	79
2	90
1	95
1	85
3	90
1	115
1	84
3	79
1	94
2	97
3	86
2	111
2	87
3	98
1	87
3	68
3	88
1	82
2	111
1	75
1	94
2	95
1	80
1	95
3	68
2	94
2	88
1	84
1	101
1	98
2	78
3	109
3	102
3	81
3	97
2	75
2	97
3	101
3	101
2	95
2	95
3	95
2	90
3	107
3	92
2	86
2	70
3	95
3	96
2	91
1	87
2	92
2	97
2	102
2	91
3	68
2	88
3	97
1	90
3	101
3	94
1	101
1	109
2	100
1	103
3	94
1	97
3	85
2	75
3	77
1	87
1	78
2	108
3	97
1	105
3	106
1	107
2	95
2	107
3	115
3	101
1	85
3	90
3	115
3	95
2	97
3	112
3	97
3	77
3	90
1	94
3	103
1	77
3	98
3	90
3	111
2	77
3	88
2	75
3	92
2	78
2	106
2	80
3	87
3	92
1	111
3	86
3	85
2	90
1	101
3	94
3	86
3	86
2	90
1	75
3	86
3	91
3	97
2	91
3	70
2	98
3	96
3	95
2	100
3	95
3	97
3	97
3	92
1	115
3	88
2	87
3	100
3	98
1	102
3	96

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'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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223224&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223224&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223224&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
MOMAGE ~ WISCRY7V
means2.3332.1432212.52222322.52331.62.251.66721.66731122.8891.8572.4292.42.22.8332.1252.2732.62.52.4

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MOMAGE  ~  WISCRY7V \tabularnewline
means & 2.333 & 2.143 & 2 & 2 & 1 & 2.5 & 2 & 2 & 2 & 2 & 3 & 2 & 2.5 & 2 & 3 & 3 & 1.6 & 2.25 & 1.667 & 2 & 1.667 & 3 & 1 & 1 & 2 & 2.889 & 1.857 & 2.429 & 2.4 & 2.2 & 2.833 & 2.125 & 2.273 & 2.6 & 2.5 & 2.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223224&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]MOMAGE  ~  WISCRY7V[/C][/ROW]
[ROW][C]means[/C][C]2.333[/C][C]2.143[/C][C]2[/C][C]2[/C][C]1[/C][C]2.5[/C][C]2[/C][C]2[/C][C]2[/C][C]2[/C][C]3[/C][C]2[/C][C]2.5[/C][C]2[/C][C]3[/C][C]3[/C][C]1.6[/C][C]2.25[/C][C]1.667[/C][C]2[/C][C]1.667[/C][C]3[/C][C]1[/C][C]1[/C][C]2[/C][C]2.889[/C][C]1.857[/C][C]2.429[/C][C]2.4[/C][C]2.2[/C][C]2.833[/C][C]2.125[/C][C]2.273[/C][C]2.6[/C][C]2.5[/C][C]2.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223224&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223224&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
MOMAGE ~ WISCRY7V
means2.3332.1432212.52222322.52331.62.251.66721.66731122.8891.8572.4292.42.22.8332.1252.2732.62.52.4






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
WISCRY7V36792.74222.02132.9220
Residuals11778.2580.669 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
WISCRY7V & 36 & 792.742 & 22.021 & 32.922 & 0 \tabularnewline
Residuals & 117 & 78.258 & 0.669 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223224&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]WISCRY7V[/C][C]36[/C][C]792.742[/C][C]22.021[/C][C]32.922[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]117[/C][C]78.258[/C][C]0.669[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223224&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223224&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)
WISCRY7V36792.74222.02132.9220
Residuals11778.2580.669






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=223224&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223224&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223224&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)
Group350.8940.639
117 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 35 & 0.894 & 0.639 \tabularnewline
  & 117 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223224&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]35[/C][C]0.894[/C][C]0.639[/C][/ROW]
[ROW][C] [/C][C]117[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223224&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223224&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)
Group350.8940.639
117


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')