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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, 01 Nov 2010 13:29:38 +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/2010/Nov/01/t1288618127n0oxh3wv9mszbtg.htm/, Retrieved Mon, 29 Apr 2024 12:23:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=90802, Retrieved Mon, 29 Apr 2024 12:23:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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)] [Golfballs] [2010-10-25 12:27:51] [b98453cac15ba1066b407e146608df68]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Question 6] [2010-11-01 13:29:38] [bff44ea937c3f909b1dc9a8bfab919e2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5	'T'
0	'T'
0	'T'
0	'T'
0	'T'
1	'T'
5	'T'
1	'T'
4	'T'
1	'T'
3	'T'
1	'T'
0	'T'
0	'T'
1	'T'
0	'T'
1	'T'
2	'T'
2	'T'
1	'T'
2	'T'
-1	'T'
3	'T'
-1	'T'
0	'T'
0	'T'
1	'T'
0	'T'
-1	'T'
4	'T'
0	'T'
1	'T'
0	'T'
0	'T'
4	'T'
2	'E'
1	'E'
4	'E'
0	'E'
4	'E'
0	'E'
0	'E'
0	'E'
5	'E'
1	'E'
0	'E'
4	'E'
4	'E'
1	'E'
1	'E'
1	'E'
4	'E'
1	'E'
3	'E'
1	'E'
5	'E'
4	'E'
0	'E'
1	'E'
4	'E'
0	'E'
-1	'E'
2	'E'
1	'E'
1	'E'
0	'E'
4	'E'
4	'E'
3	'S'
1	'S'
1	'S'
5	'S'
0	'S'
-1	'S'
1	'S'
2	'S'
-1	'S'
2	'S'
0	'S'
4	'S'
4	'S'
-1	'S'
0	'S'
4	'S'
-1	'S'
4	'S'
2	'S'
2	'S'
0	'S'
0	'S'
4	'S'
1	'S'
0	'S'
0	'S'
4	'S'
4	'S'
0	'S'
0	'S'
2	'S'
1	'S'
0	'S'
2	'S'
2	'S'

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 Ronald Aylmer Fisher' @ 193.190.124.24

\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 Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=90802&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 Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=90802&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=90802&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 Ronald Aylmer Fisher' @ 193.190.124.24






ANOVA Model
Tot-pre ~ Treatment
means1.879-0.422-0.736

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Tot-pre  ~  Treatment \tabularnewline
means & 1.879 & -0.422 & -0.736 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=90802&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Tot-pre  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]1.879[/C][C]-0.422[/C][C]-0.736[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=90802&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=90802&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-pre ~ Treatment
means1.879-0.422-0.736






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment29.2424.6211.4980.229
Residuals100308.4873.085 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 2 & 9.242 & 4.621 & 1.498 & 0.229 \tabularnewline
Residuals & 100 & 308.487 & 3.085 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=90802&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]9.242[/C][C]4.621[/C][C]1.498[/C][C]0.229[/C][/ROW]
[ROW][C]Residuals[/C][C]100[/C][C]308.487[/C][C]3.085[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=90802&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=90802&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)
Treatment29.2424.6211.4980.229
Residuals100308.4873.085






Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-E-0.422-1.4360.5920.585
T-E-0.736-1.750.2780.2
T-S-0.314-1.3130.6850.735

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-E & -0.422 & -1.436 & 0.592 & 0.585 \tabularnewline
T-E & -0.736 & -1.75 & 0.278 & 0.2 \tabularnewline
T-S & -0.314 & -1.313 & 0.685 & 0.735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=90802&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]-0.422[/C][C]-1.436[/C][C]0.592[/C][C]0.585[/C][/ROW]
[ROW][C]T-E[/C][C]-0.736[/C][C]-1.75[/C][C]0.278[/C][C]0.2[/C][/ROW]
[ROW][C]T-S[/C][C]-0.314[/C][C]-1.313[/C][C]0.685[/C][C]0.735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=90802&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=90802&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-E-0.422-1.4360.5920.585
T-E-0.736-1.750.2780.2
T-S-0.314-1.3130.6850.735






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.5470.58
100 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.547 & 0.58 \tabularnewline
  & 100 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=90802&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]0.547[/C][C]0.58[/C][/ROW]
[ROW][C] [/C][C]100[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=90802&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=90802&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)
Group20.5470.58
100


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')