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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, 07 Nov 2011 08:57:40 -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/Nov/07/t132067428407p1alenwpmof3v.htm/, Retrieved Thu, 18 Apr 2024 09:40:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=140171, Retrieved Thu, 18 Apr 2024 09:40:51 +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)] [Workshop 5_Vraag ...] [2011-11-07 13:57:40] [3e64eea457df40fcb7af8f28e1ee6256] [Current]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Workshop 5_ Vraag 7] [2011-11-07 14:06:36] [f722e8e78b9e5c5ebaa2263f273aa636]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Workshop 5_ Vraag 7] [2011-11-07 14:08:06] [f722e8e78b9e5c5ebaa2263f273aa636]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Workshop 5: Task ...] [2011-11-07 19:07:10] [74be16979710d4c4e7c6647856088456]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Workshop 5: Task ...] [2011-11-07 19:07:10] [74be16979710d4c4e7c6647856088456]
- RMPD    [Two-Way ANOVA] [Workshop 5: Task 8] [2011-11-07 20:15:46] [f722e8e78b9e5c5ebaa2263f273aa636]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	'T'
1	'T'
1.5	'T'
0	'T'
0	'T'
1	'T'
1	'T'
1	'T'
2	'T'
1	'T'
2	'T'
0	'T'
0	'T'
2	'T'
NA	'T'
1	'T'
1	'T'
-0.5	'T'
2	'T'
0	'T'
1	'T'
-1	'T'
NA	'T'
NA	'T'
1	'T'
-1	'T'
NA	'T'
NA	'T'
2	'T'
0	'T'
-0.5	'T'
1	'T'
0.5	'T'
NA	'T'
0.5	'T'
NA	'T'
1	'T'
0	'E'
1	'E'
1	'E'
0	'E'
1	'E'
-1	'E'
-0.5	'E'
0	'E'
2	'E'
0	'E'
0	'E'
1	'E'
0.5	'E'
2	'E'
1	'E'
2	'E'
NA	'E'
0	'E'
0	'E'
0.5	'E'
NA	'E'
2	'E'
NA	'E'
0	'E'
1	'E'
0	'E'
-1	'E'
2	'E'
1	'E'
2	'E'
0	'E'
0	'E'
1	'E'
0	'S'
0	'S'
0	'S'
0	'S'
1	'S'
1	'S'
2	'S'
1	'S'
1	'S'
1	'S'
2	'S'
2	'S'
2	'S'
1	'S'
NA	'S'
2	'S'
NA	'S'
1	'S'
2	'S'
NA	'S'
-1	'S'
1	'S'
NA	'S'
2	'S'
1	'S'
1	'S'
1	'S'
1	'S'
NA	'S'
0	'S'
-1	'S'
2	'S'
0	'S'
2	'S'
0	'S'

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=140171&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=140171&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140171&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
post4-pre ~ Treatment
means0.6170.3170.1

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post4-pre  ~  Treatment \tabularnewline
means & 0.617 & 0.317 & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140171&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post4-pre  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]0.617[/C][C]0.317[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140171&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140171&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
post4-pre ~ Treatment
means0.6170.3170.1






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment21.5720.7860.990.376
Residuals8769.050.794 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 2 & 1.572 & 0.786 & 0.99 & 0.376 \tabularnewline
Residuals & 87 & 69.05 & 0.794 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140171&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]2[/C][C]1.572[/C][C]0.786[/C][C]0.99[/C][C]0.376[/C][/ROW]
[ROW][C]Residuals[/C][C]87[/C][C]69.05[/C][C]0.794[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140171&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140171&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)
Treatment21.5720.7860.990.376
Residuals8769.050.794






Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-E0.317-0.2320.8650.358
T-E0.1-0.4480.6480.901
T-S-0.217-0.7650.3320.615

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-E & 0.317 & -0.232 & 0.865 & 0.358 \tabularnewline
T-E & 0.1 & -0.448 & 0.648 & 0.901 \tabularnewline
T-S & -0.217 & -0.765 & 0.332 & 0.615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140171&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]S-E[/C][C]0.317[/C][C]-0.232[/C][C]0.865[/C][C]0.358[/C][/ROW]
[ROW][C]T-E[/C][C]0.1[/C][C]-0.448[/C][C]0.648[/C][C]0.901[/C][/ROW]
[ROW][C]T-S[/C][C]-0.217[/C][C]-0.765[/C][C]0.332[/C][C]0.615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140171&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140171&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
S-E0.317-0.2320.8650.358
T-E0.1-0.4480.6480.901
T-S-0.217-0.7650.3320.615






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.2570.774
87 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.257 & 0.774 \tabularnewline
  & 87 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140171&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]0.257[/C][C]0.774[/C][/ROW]
[ROW][C] [/C][C]87[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140171&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140171&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)
Group20.2570.774
87


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; 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){
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')