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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, 11 Dec 2014 22:40:13 +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/11/t1418337644tjn3hxiw25bwbkp.htm/, Retrieved Thu, 16 May 2024 19:59:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266402, Retrieved Thu, 16 May 2024 19:59:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

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)] [bow II] [2014-12-11 22:40:13] [7ba19d107fbc5e986bea1d115fcbe5dd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 50
0 62
1 54
0 71
1 54
1 65
1 73
0 52
1 84
1 42
1 66
1 65
1 78
1 73
0 75
0 72
0 66
1 70
0 61
1 81
0 71
1 69
1 71
0 72
1 68
1 70
1 68
1 61
0 67
1 76
0 70
0 60
1 72
1 69
1 71
1 62
1 70
0 64
1 58
1 76
0 52
1 59
1 68
1 76
1 65
1 67
0 59
1 69
1 76
0 63
1 75
1 63
1 60
1 73
1 63
1 70
1 75
0 66
1 63
0 63
1 64
1 70
0 75
0 61
1 60
0 62
1 73
0 61
1 66
1 64
0 59
0 64
0 60
0 56
1 78
1 67
0 59
1 66
0 68
0 71
1 66
0 73
0 72
0 71
1 59
0 64
1 66
1 78
0 68
0 73
0 62
1 65
1 68
1 65
0 60
1 71
0 65
1 68
1 64
1 74
1 69
1 76
0 68
1 72
1 67
1 63
0 59
0 73
0 66
0 62
0 69
0 66
1 51
1 56
1 67
1 69
1 57
0 56
1 55
1 63
0 67
1 65
0 47
0 76
1 64
1 68
1 64
1 65
1 71
1 63
1 60
1 68
0 72
1 70
1 61
1 61
1 62
1 71
1 71
0 51
1 56
1 70
1 73
1 76
0 68
0 48
0 52
0 60
0 59
0 57
1 79
0 60
1 60
1 59
0 62
1 59
1 61
1 71
0 57
0 66
0 63
0 69
1 58
0 59
1 48
0 66
1 73
0 67
1 61
0 68
0 75
1 62
0 69
1 58
1 60
1 74
1 55
1 62
0 63
1 69
0 58
0 58
0 68
1 72
0 62
1 62
0 65
0 69
0 66
0 72
1 62
1 75
1 58
1 66
0 55
0 47
1 72
0 62
0 64
0 64
0 19
1 50
1 68
0 70
0 79
1 69
0 71
1 48
1 73
0 74
1 66
1 71
1 74
0 78
0 75
0 53
1 60
0 70
1 69
1 65
0 78
0 78
0 59
1 72
1 70
0 63
0 63
0 71
1 74
1 67
0 66
0 62
0 80
1 73
1 67
1 61
1 73
0 74
1 32
1 69
1 69
0 84
0 64
1 58
1 59
1 78
1 57
0 60
1 68
0 68
1 73
1 69
0 67
1 60
0 65
1 66
0 74
1 81
0 72
0 55
1 49
1 74
0 53
1 64
1 65
0 57
1 51
0 80
0 67
1 70
1 74
0 75
1 70
0 69
0 65
1 55
0 71
0 65

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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266402&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266402&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266402&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 Ronald Aylmer Fisher' @ fisher.wessa.net






ANOVA Model
AMS.E ~ gender
means64.951.069

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
AMS.E  ~  gender \tabularnewline
means & 64.95 & 1.069 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266402&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]AMS.E  ~  gender[/C][/ROW]
[ROW][C]means[/C][C]64.95[/C][C]1.069[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266402&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266402&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
AMS.E ~ gender
means64.951.069






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
gender177.93677.9361.1740.28
Residuals27618320.64366.379 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
gender & 1 & 77.936 & 77.936 & 1.174 & 0.28 \tabularnewline
Residuals & 276 & 18320.643 & 66.379 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266402&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]77.936[/C][C]77.936[/C][C]1.174[/C][C]0.28[/C][/ROW]
[ROW][C]Residuals[/C][C]276[/C][C]18320.643[/C][C]66.379[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266402&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266402&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)
gender177.93677.9361.1740.28
Residuals27618320.64366.379






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-01.069-0.8733.0110.28

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 1.069 & -0.873 & 3.011 & 0.28 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266402&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]1.069[/C][C]-0.873[/C][C]3.011[/C][C]0.28[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266402&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266402&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
1-01.069-0.8733.0110.28






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.1110.739
276 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.111 & 0.739 \tabularnewline
  & 276 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266402&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]0.111[/C][C]0.739[/C][/ROW]
[ROW][C] [/C][C]276[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266402&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266402&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)
Group10.1110.739
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')