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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, 05 Nov 2013 15:38:33 -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/2013/Nov/05/t1383684038ujsiajo85s80w51.htm/, Retrieved Sun, 28 Apr 2024 23:38:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=222844, Retrieved Sun, 28 Apr 2024 23:38:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

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 Task 7] [2013-11-05 20:38:33] [9e345f4af24c955bbdd99e7ffb840b0f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0 0
0 0
1 2
0 0
1 2
0 1
0 0
1 2
0 0
0 0
0 0
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0 NA
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0 NA
-1 -1
0 0
0 1
1 1
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1 2
0 0
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1 1
1 1
0 1
1 1
1 1
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0 NA
0 1
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-1 NA
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1 NA
1 1
0 0
0 0
0 1
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1 1
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1 NA
1 1
1 NA
0 0
1 1
0 NA
1 1
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1 1
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0 0
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0 0
0 1
0 0
0 NA
0 0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222844&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]3 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=222844&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222844&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
Exp2_post1-pre ~ Exp2_tot-pre
means-111.62921.2

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Exp2_post1-pre  ~  Exp2_tot-pre \tabularnewline
means & -1 & 1 & 1.629 & 2 & 1.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222844&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Exp2_post1-pre  ~  Exp2_tot-pre[/C][/ROW]
[ROW][C]means[/C][C]-1[/C][C]1[/C][C]1.629[/C][C]2[/C][C]1.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222844&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222844&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
Exp2_post1-pre ~ Exp2_tot-pre
means-111.62921.2






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Exp2_tot-pre415.423.85535.2650
Residuals11512.5710.109 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Exp2_tot-pre & 4 & 15.42 & 3.855 & 35.265 & 0 \tabularnewline
Residuals & 115 & 12.571 & 0.109 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222844&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]Exp2_tot-pre[/C][C]4[/C][C]15.42[/C][C]3.855[/C][C]35.265[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]115[/C][C]12.571[/C][C]0.109[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222844&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222844&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)
Exp2_tot-pre415.423.85535.2650
Residuals11512.5710.109






Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--110.3421.6580
1--11.6290.9622.2950
2--121.2522.7480
NA--11.20.511.890
1-00.6290.4350.8220
2-010.6081.3920
NA-00.2-0.0640.4640.226
2-10.371-0.0330.7760.088
NA-1-0.429-0.711-0.1460
NA-2-0.8-1.243-0.3570

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & 1 & 0.342 & 1.658 & 0 \tabularnewline
1--1 & 1.629 & 0.962 & 2.295 & 0 \tabularnewline
2--1 & 2 & 1.252 & 2.748 & 0 \tabularnewline
NA--1 & 1.2 & 0.51 & 1.89 & 0 \tabularnewline
1-0 & 0.629 & 0.435 & 0.822 & 0 \tabularnewline
2-0 & 1 & 0.608 & 1.392 & 0 \tabularnewline
NA-0 & 0.2 & -0.064 & 0.464 & 0.226 \tabularnewline
2-1 & 0.371 & -0.033 & 0.776 & 0.088 \tabularnewline
NA-1 & -0.429 & -0.711 & -0.146 & 0 \tabularnewline
NA-2 & -0.8 & -1.243 & -0.357 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222844&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]0--1[/C][C]1[/C][C]0.342[/C][C]1.658[/C][C]0[/C][/ROW]
[ROW][C]1--1[/C][C]1.629[/C][C]0.962[/C][C]2.295[/C][C]0[/C][/ROW]
[ROW][C]2--1[/C][C]2[/C][C]1.252[/C][C]2.748[/C][C]0[/C][/ROW]
[ROW][C]NA--1[/C][C]1.2[/C][C]0.51[/C][C]1.89[/C][C]0[/C][/ROW]
[ROW][C]1-0[/C][C]0.629[/C][C]0.435[/C][C]0.822[/C][C]0[/C][/ROW]
[ROW][C]2-0[/C][C]1[/C][C]0.608[/C][C]1.392[/C][C]0[/C][/ROW]
[ROW][C]NA-0[/C][C]0.2[/C][C]-0.064[/C][C]0.464[/C][C]0.226[/C][/ROW]
[ROW][C]2-1[/C][C]0.371[/C][C]-0.033[/C][C]0.776[/C][C]0.088[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.429[/C][C]-0.711[/C][C]-0.146[/C][C]0[/C][/ROW]
[ROW][C]NA-2[/C][C]-0.8[/C][C]-1.243[/C][C]-0.357[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222844&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222844&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
0--110.3421.6580
1--11.6290.9622.2950
2--121.2522.7480
NA--11.20.511.890
1-00.6290.4350.8220
2-010.6081.3920
NA-00.2-0.0640.4640.226
2-10.371-0.0330.7760.088
NA-1-0.429-0.711-0.1460
NA-2-0.8-1.243-0.3570






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group49.4840
115 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 9.484 & 0 \tabularnewline
  & 115 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222844&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]4[/C][C]9.484[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]115[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222844&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222844&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)
Group49.4840
115


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){
'Tukey Plot'
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<-leveneTest(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')