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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 computationTue, 02 Nov 2010 17:04:43 +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/t12887174080gq1mu2ui5n8owh.htm/, Retrieved Sun, 28 Apr 2024 17:01:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91863, Retrieved Sun, 28 Apr 2024 17:01:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

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)] [WS5: Vraag 6] [2010-10-29 08:56:06] [1fd136673b2a4fecb5c545b9b4a05d64]
-         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Taak 6: One way A...] [2010-10-29 11:07:09] [74deae64b71f9d77c839af86f7c687b5]
F    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Taak 7: treatment...] [2010-10-29 13:58:26] [74deae64b71f9d77c839af86f7c687b5]
-             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q7] [2010-11-02 11:58:57] [afe9379cca749d06b3d6872e02cc47ed]
F R P             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS 5 Q 7] [2010-11-02 17:04:43] [7131fefee4115a2a717140ef0bdd6369] [Current]
Feedback Forum
2010-11-07 17:39:49 [Sandra Claessens] [reply] 
De student gebruikte niet genoeg data en kwam hierdoor tot een foute oplossing. Ook veranderde de student hier tevens de intercept van true naar false. Als we kijken naar de links van de voorbeeldoplossing dan zien we dat treatment CSWE de beste treatment is op korte termijn. Als we kijken naar de voorbeeldoplossing voor lange termijn zien we dat er op lange termijn geen effect is. De scores van de studenten die ‘C’ als treatment hebben gehad stijgen zeer lichtjes maar de stijging is niet significant genoeg. We zien hetzelfde bij treatment ‘WWW’.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
-1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'CSWE'
-1	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'C'
0	'C'
-1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
1	'C'
0	'C'
0	'C'
0	'C'
1	'C'
1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
1	'C'
0	'C'
1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91863&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91863&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91863&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'RServer@AstonUniversity' @ vre.aston.ac.uk






ANOVA Model
A ~ B
means0.1030.3750.244

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
A  ~  B \tabularnewline
means & 0.103 & 0.375 & 0.244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91863&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]A  ~  B[/C][/ROW]
[ROW][C]means[/C][C]0.103[/C][C]0.375[/C][C]0.244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91863&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91863&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
A ~ B
means0.1030.3750.244






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
B38.4742.82512.4590
Residuals11726.5260.227 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
B & 3 & 8.474 & 2.825 & 12.459 & 0 \tabularnewline
Residuals & 117 & 26.526 & 0.227 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91863&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[/C][C]3[/C][C]8.474[/C][C]2.825[/C][C]12.459[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]117[/C][C]26.526[/C][C]0.227[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91863&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91863&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)
B38.4742.82512.4590
Residuals11726.5260.227






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=91863&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91863&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91863&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)
Group23.6390.029
117 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 3.639 & 0.029 \tabularnewline
  & 117 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91863&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]3.639[/C][C]0.029[/C][/ROW]
[ROW][C] [/C][C]117[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91863&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91863&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)
Group23.6390.029
117


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){
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')