FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 02 Nov 2010 20:55:43 +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/02/t12887312617j1ng26h5kzsiwj.htm/, Retrieved Sat, 27 Apr 2024 15:49:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=92072, Retrieved Sat, 27 Apr 2024 15:49:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167

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]
F   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-02 20:55:43] [7b390cc0228d34e5578246b07143e3df] [Current]
Feedback Forum
2010-11-06 21:47:50 [411b43619fc9db329bbcdbf7261c55fb] [reply] 
Bij de analyse op lange termijn heeft de auteur weer de NA’s vervangen door lege cellen. Hierdoor krijgt de auteur een ander resultaat bij zijn berekening (bekijk http://www.freestatistics.org/blog/index.php?v=date/2010/Nov/06/t1289073626y7p31y740w0s1m7.htm/ voor de berekening met de NA’s). Hij geeft ook de verkeerde conclusie. Ik stel de volgende conclusie voor (op basis van mijn link): Er is geen verschil merkbaar op lange termijn (bij de 3 vergelijkingen van de treatments is er telkens een hoge p-waarde = dus een hoge kans op vergissen bij het verwerpen van de nulhypothese). De rede hiervoor is dat er geen rekening wordt gehouden met de inspanning van de student. Men zegt dus niks over de efficiëntie van het leren.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'T'	-1
'T'	-1
'T'	1
'T'	0
'T'	0
'T'	0
'T'	0
'T'	1
'T'	1
'T'	-1
'T'	0
'T'	1
'T'	1
'T'	0
'T'	
'T'	0
'T'	-1
'T'	0
'T'	1
'T'	1
'T'	0
'T'	-1
'T'	
'T'	
'T'	0
'T'	0
'T'	
'T'	
'T'	0
'T'	0
'T'	-1
'T'	-1
'T'	1
'T'	
'T'	1
'T'	
'T'	-1
'E'	1
'E'	1
'E'	0
'E'	0
'E'	0
'E'	-1
'E'	0
'E'	1
'E'	1
'E'	0
'E'	-1
'E'	0
'E'	0
'E'	1
'E'	0
'E'	1
'E'	
'E'	0
'E'	1
'E'	1
'E'	
'E'	0
'E'	
'E'	1
'E'	0
'E'	0
'E'	0
'E'	1
'E'	0
'E'	1
'E'	0
'E'	0
'E'	0
'S'	0
'S'	0
'S'	0
'S'	0
'S'	0
'S'	0
'S'	1
'S'	0
'S'	0
'S'	0
'S'	1
'S'	1
'S'	1
'S'	0
'S'	
'S'	1
'S'	
'S'	0
'S'	1
'S'	
'S'	-1
'S'	0
'S'	
'S'	1
'S'	0
'S'	0
'S'	0
'S'	0
'S'	
'S'	0
'S'	-1
'S'	1
'S'	0
'S'	1
'S'	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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92072&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92072&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92072&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' @ 72.249.127.135






ANOVA Model
Treatment ~ Pos
means0.167-0.042-0.258

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Treatment  ~  Pos \tabularnewline
means & 0.167 & -0.042 & -0.258 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92072&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Treatment  ~  Pos[/C][/ROW]
[ROW][C]means[/C][C]0.167[/C][C]-0.042[/C][C]-0.258[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92072&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92072&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
Treatment ~ Pos
means0.167-0.042-0.258






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Pos20.7230.3620.7020.501
Residuals4523.1930.515 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Pos & 2 & 0.723 & 0.362 & 0.702 & 0.501 \tabularnewline
Residuals & 45 & 23.193 & 0.515 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92072&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]Pos[/C][C]2[/C][C]0.723[/C][C]0.362[/C][C]0.702[/C][C]0.501[/C][/ROW]
[ROW][C]Residuals[/C][C]45[/C][C]23.193[/C][C]0.515[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92072&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92072&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)
Pos20.7230.3620.7020.501
Residuals4523.1930.515






Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-E-0.042-0.7810.6980.99
T-E-0.258-0.8110.2950.502
T-S-0.216-0.9340.5020.748

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-E & -0.042 & -0.781 & 0.698 & 0.99 \tabularnewline
T-E & -0.258 & -0.811 & 0.295 & 0.502 \tabularnewline
T-S & -0.216 & -0.934 & 0.502 & 0.748 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92072&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]-0.042[/C][C]-0.781[/C][C]0.698[/C][C]0.99[/C][/ROW]
[ROW][C]T-E[/C][C]-0.258[/C][C]-0.811[/C][C]0.295[/C][C]0.502[/C][/ROW]
[ROW][C]T-S[/C][C]-0.216[/C][C]-0.934[/C][C]0.502[/C][C]0.748[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92072&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92072&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-0.042-0.7810.6980.99
T-E-0.258-0.8110.2950.502
T-S-0.216-0.9340.5020.748






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.3240.725
45 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.324 & 0.725 \tabularnewline
  & 45 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92072&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]0.324[/C][C]0.725[/C][/ROW]
[ROW][C] [/C][C]45[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92072&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92072&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)
Group20.3240.725
45


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; 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')