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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 computationWed, 17 Dec 2014 09:23:06 +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/17/t1418808200x6emrgrset8o5fd.htm/, Retrieved Thu, 16 May 2024 09:21:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269997, Retrieved Thu, 16 May 2024 09:21:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

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)] [f] [2014-12-17 09:23:06] [32fa21232fc319032ead83218c7d01c8] [Current]
- RMPD    [Notched Boxplots] [cjdfj] [2014-12-17 10:39:29] [e596eb22b7565c1d1947422243452583]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11.3 1
9.6 1
16.1 1
13.4 1
12.7 1
12.3 1
7.9 1
12.3 1
11.6 1
6.7 1
12.1 1
5.7 1
8 1
13.3 1
9.1 1
12.2 1
8.8 1
14.6 1
12.6 1
9.9 1
10.5 1
13.4 1
10.9 1
4.3 1
10.3 1
11.8 1
11.2 1
11.4 1
8.6 1
13.2 1
12.6 1
5.6 1
9.9 1
8.8 1
7.7 1
9 1
7.3 1
11.4 1
13.6 1
7.9 1
10.7 1
10.3 1
8.3 1
9.6 1
14.2 1
8.5 1
13.5 1
4.9 1
6.4 1
9.6 1
11.6 1
11.1 1
16.6 1
12.6 1
18.9 1
11.6 1
14.6 1
13.85 1
14.85 1
11.75 1
18.45 1
15.9 1
19.9 1
10.95 1
18.45 1
15.1 1
15 1
11.35 1
15.95 1
18.1 1
14.6 1
17.6 1
15.35 1
13.4 1
13.9 1
15.25 1
12.9 1
16.1 1
17.35 1
13.15 1
12.15 1
12.6 1
10.35 1
15.4 1
9.6 1
18.2 1
13.6 1
14.85 1
14.1 1
14.9 1
16.25 1
13.6 1
15.65 1
14.6 1
12.65 1
11.9 1
19.2 1
16.6 1
11.2 1
13.2 1
15.85 1
11.15 1
15.65 1
7.65 1
15.2 1
15.6 1
13.1 1
11.85 1
12.4 1
11.4 1
14.9 1
19.9 1
11.2 1
14.6 1
14.75 1
15.15 1
16.85 1
7.85 1
12.6 1
7.85 1
10.95 1
12.35 1
9.95 1
14.9 1
16.65 1
13.4 1
13.95 1
15.7 1
16.85 1
10.95 1
15.35 1
12.2 1
15.1 1
17.75 1
15.2 1
16.65 1
8.1 1
12.9 0
7.4 0
12.2 0
12.8 0
7.4 0
6.7 0
12.6 0
14.8 0
13.3 0
11.1 0
8.2 0
11.4 0
6.4 0
10.6 0
12 0
6.3 0
11.9 0
9.3 0
10 0
6.4 0
13.8 0
10.8 0
13.8 0
11.7 0
10.9 0
9.9 0
11.5 0
8.3 0
11.7 0
6.1 0
9 0
9.7 0
10.8 0
10.3 0
10.4 0
9.3 0
11.8 0
5.9 0
11.4 0
13 0
10.8 0
11.3 0
11.8 0
12.7 0
10.9 0
13.3 0
10.1 0
14.3 0
9.3 0
12.5 0
7.6 0
15.9 0
9.2 0
11.1 0
13 0
14.5 0
12.3 0
11.4 0
7.3 0
12.6 0
13 0
13.2 0
7.7 0
4.35 0
12.7 0
18.1 0
17.85 0
17.1 0
19.1 0
16.1 0
13.35 0
18.4 0
14.7 0
10.6 0
12.6 0
16.2 0
13.6 0
14.1 0
14.5 0
16.15 0
14.75 0
14.8 0
12.45 0
12.65 0
17.35 0
8.6 0
18.4 0
16.1 0
17.75 0
15.25 0
17.65 0
15.6 0
16.35 0
17.65 0
13.6 0
11.7 0
14.35 0
14.75 0
18.25 0
9.9 0
16 0
18.25 0
16.85 0
18.95 0
15.6 0
17.1 0
16.1 0
15.4 0
15.4 0
13.35 0
19.1 0
7.6 0
19.1 0
14.75 0
19.25 0
13.6 0
12.75 0
9.85 0
15.25 0
11.9 0
16.35 0
12.4 0
14.35 0
18.15 0
17.75 0
12.35 0
15.6 0
19.3 0
17.1 0
18.4 0
19.05 0
18.55 0
19.1 0
12.85 0
9.5 0
4.5 0
13.6 0
11.7 0
13.35 0
17.75 0
17.6 0
14.05 0
16.1 0
13.35 0
11.85 0
11.95 0
13.2 0
7.7 0
14.6 0

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269997&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269997&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269997&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'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
TOT ~ B/S
means13.12212.729

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
TOT  ~  B/S \tabularnewline
means & 13.122 & 12.729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269997&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]TOT  ~  B/S[/C][/ROW]
[ROW][C]means[/C][C]13.122[/C][C]12.729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269997&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269997&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 ~ B/S
means13.12212.729






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
B/S247856.18223928.0912043.8440
Residuals2843324.911.707 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
B/S & 2 & 47856.182 & 23928.091 & 2043.844 & 0 \tabularnewline
Residuals & 284 & 3324.9 & 11.707 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269997&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]B/S[/C][C]2[/C][C]47856.182[/C][C]23928.091[/C][C]2043.844[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]284[/C][C]3324.9[/C][C]11.707[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269997&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269997&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)
B/S247856.18223928.0912043.8440
Residuals2843324.911.707






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=269997&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269997&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269997&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)
Group10.7340.392
284 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.734 & 0.392 \tabularnewline
  & 284 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269997&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]0.734[/C][C]0.392[/C][/ROW]
[ROW][C] [/C][C]284[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269997&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269997&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)
Group10.7340.392
284


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')