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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, 22 Dec 2011 08:49:48 -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/2011/Dec/22/t1324561797mf6zivzwb4t1jwc.htm/, Retrieved Fri, 03 May 2024 14:53:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159455, Retrieved Fri, 03 May 2024 14:53:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

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)] [deel 1 anova LT] [2011-12-21 09:48:16] [845a0512200c8372fa3331a361537afe]
- R PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [lt] [2011-12-22 13:49:48] [7079f287d9c11563cf2e6921d61ac78d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	4	0	2	'T'	0	3	-1	1
1	1	0	0	2	'T'	0	-1	-1	1
0	1	4	1	1.5	'T'	1	4	1	1.5
0	0	0	0	0	'T'	0	0	0	0
1	1	0	1	1	'T'	0	-1	0	0
1	1	0	1	2	'T'	0	-1	0	1
1	1	0	1	2	'T'	0	-1	0	1
0	1	0	1	1	'T'	1	0	1	1
0	1	4	1	2	'T'	1	4	1	2
1	1	1	0	2	'T'	0	0	-1	1
0	0	4	0	2	'T'	0	4	0	2
0	1	0	1	0	'T'	1	0	1	0
0	1	2	1	0	'T'	1	2	1	0
0	1	0	0	2	'T'	1	0	0	2
0	0	0	NA	NA	'T'	0	0	NA	NA
1	1	0	1	2	'T'	0	-1	0	1
1	1	1	0	2	'T'	0	0	-1	1
1	1	0	1	0.5	'T'	0	-1	0	-0.5
0	1	0	1	2	'T'	1	0	1	2
0	0	2	1	0	'T'	0	2	1	0
1	1	2	1	2	'T'	0	1	0	1
1	1	1	0	0	'T'	0	0	-1	-1
0	0	2	NA	NA	'T'	0	2	NA	NA
1	0	0	NA	NA	'T'	-1	-1	NA	NA
1	1	3	1	2	'T'	0	2	0	1
1	0	0	1	0	'T'	-1	-1	0	-1
1	1	0	NA	NA	'T'	0	-1	NA	NA
0	0	0	NA	NA	'T'	0	0	NA	NA
0	0	1	0	2	'T'	0	1	0	2
1	1	0	1	1	'T'	0	-1	0	0
1	0	0	0	0.5	'T'	-1	-1	-1	-0.5
1	1	4	0	2	'T'	0	3	-1	1
0	0	0	1	0.5	'T'	0	0	1	0.5
0	0	1	NA	NA	'T'	0	1	NA	NA
0	0	0	1	0.5	'T'	0	0	1	0.5
1	1	0	NA	NA	'T'	0	-1	NA	NA
1	1	4	0	2	'T'	0	3	-1	1
0	1	1	1	0	'E'	1	1	1	0
0	1	0	1	1	'E'	1	0	1	1
1	1	4	1	2	'E'	0	3	0	1
1	1	0	1	1	'E'	0	-1	0	0
1	1	4	1	2	'E'	0	3	0	1
1	1	0	0	0	'E'	0	-1	-1	-1
1	1	0	1	0.5	'E'	0	-1	0	-0.5
0	0	0	1	0	'E'	0	0	1	0
0	1	4	1	2	'E'	1	4	1	2
0	1	0	0	0	'E'	1	0	0	0
1	1	0	0	1	'E'	0	-1	-1	0
1	1	4	1	2	'E'	0	3	0	1
0	0	4	0	0.5	'E'	0	4	0	0.5
0	1	0	1	2	'E'	1	0	1	2
1	1	1	1	2	'E'	0	0	0	1
0	1	0	1	2	'E'	1	0	1	2
0	0	4	NA	NA	'E'	0	4	NA	NA
0	1	0	0	0	'E'	1	0	0	0
0	1	2	1	0	'E'	1	2	1	0
0	1	0	1	0.5	'E'	1	0	1	0.5
0	1	4	NA	NA	'E'	1	4	NA	NA
0	0	4	0	2	'E'	0	4	0	2
0	0	0	NA	NA	'E'	0	0	NA	NA
0	1	0	1	0	'E'	1	0	1	0
1	1	4	1	2	'E'	0	3	0	1
1	1	0	1	1	'E'	0	-1	0	0
1	0	0	1	0	'E'	-1	-1	0	-1
0	0	2	1	2	'E'	0	2	1	2
0	1	0	0	1	'E'	1	0	0	1
0	1	0	1	2	'E'	1	0	1	2
0	0	0	0	0	'E'	0	0	0	0
1	1	4	1	1	'E'	0	3	0	0
1	1	4	1	2	'E'	0	3	0	1
0	1	2	0	0	'S'	1	2	0	0
0	1	0	0	0	'S'	1	0	0	0
0	1	0	0	0	'S'	1	0	0	0
0	1	4	0	0	'S'	1	4	0	0
1	1	0	1	2	'S'	0	-1	0	1
1	0	0	1	2	'S'	-1	-1	0	1
0	0	1	1	2	'S'	0	1	1	2
1	1	2	1	2	'S'	0	1	0	1
1	0	0	1	2	'S'	-1	-1	0	1
1	1	2	1	2	'S'	0	1	0	1
0	0	0	1	2	'S'	0	0	1	2
0	0	4	1	2	'S'	0	4	1	2
0	0	4	1	2	'S'	0	4	1	2
1	0	0	1	2	'S'	-1	-1	0	1
0	0	0	NA	NA	'S'	0	0	NA	NA
0	0	4	1	2	'S'	0	4	1	2
1	0	0	NA	NA	'S'	-1	-1	NA	NA
1	1	4	1	2	'S'	0	3	0	1
0	0	2	1	2	'S'	0	2	1	2
0	0	2	NA	NA	'S'	0	2	NA	NA
1	1	0	0	0	'S'	0	-1	-1	-1
1	1	0	1	2	'S'	0	-1	0	1
1	1	4	NA	NA	'S'	0	3	NA	NA
0	1	0	1	2	'S'	1	0	1	2
1	1	0	1	2	'S'	0	-1	0	1
1	1	0	1	2	'S'	0	-1	0	1
1	1	4	1	2	'S'	0	3	0	1
1	1	4	1	2	'S'	0	3	0	1
0	0	0	NA	NA	'S'	0	0	NA	NA
0	0	0	0	0	'S'	0	0	0	0
1	1	2	0	0	'S'	0	1	-1	-1
0	0	1	1	2	'S'	0	1	1	2
0	0	0	0	0	'S'	0	0	0	0
0	0	2	1	2	'S'	0	2	1	2
0	1	1	0	0	'S'	1	1	0	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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159455&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159455&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159455&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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






ANOVA Model
post3-pre ~ Treatment
means0.30.2330.033

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post3-pre  ~  Treatment \tabularnewline
means & 0.3 & 0.233 & 0.033 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159455&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post3-pre  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]0.3[/C][C]0.233[/C][C]0.033[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159455&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159455&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
post3-pre ~ Treatment
means0.30.2330.033






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment34.3671.4563.4570.02
Residuals8736.6330.421 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 3 & 4.367 & 1.456 & 3.457 & 0.02 \tabularnewline
Residuals & 87 & 36.633 & 0.421 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159455&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]Treatment[/C][C]3[/C][C]4.367[/C][C]1.456[/C][C]3.457[/C][C]0.02[/C][/ROW]
[ROW][C]Residuals[/C][C]87[/C][C]36.633[/C][C]0.421[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159455&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159455&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)
Treatment34.3671.4563.4570.02
Residuals8736.6330.421






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=159455&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159455&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159455&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)
Group21.2470.292
87 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.247 & 0.292 \tabularnewline
  & 87 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159455&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]2[/C][C]1.247[/C][C]0.292[/C][/ROW]
[ROW][C] [/C][C]87[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159455&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159455&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)
Group21.2470.292
87


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 9 ; par2 = 6 ; par3 = FALSE ;
Parameters (R input):
par1 = 9 ; par2 = 6 ; 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){
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<-levene.test(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')