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 computationWed, 17 Dec 2014 16:36:34 +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/2014/Dec/17/t1418834203tjuvfrojlq3npwg.htm/, Retrieved Thu, 16 May 2024 21:13:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270512, Retrieved Thu, 16 May 2024 21:13:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

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)] [dfg] [2014-12-17 16:34:22] [1601e79f56036968990446024a6397e5]
- R       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [gg] [2014-12-17 16:36:34] [e3ddd9a57cdbfec6dbe72df2938debe0] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 7.5
1 2.5
1 6.0
1 6.5
1 1.0
1 1.0
1 5.5
1 8.5
1 6.5
1 4.5
1 2.0
1 5.0
1 0.5
1 5.0
1 5.0
1 2.5
0 5.0
1 5.5
1 3.5
0 3.0
1 4.0
1 0.5
1 6.5
1 4.5
1 7.5
1 5.5
1 4.0
0 7.5
0 7.0
1 4.0
1 5.5
1 2.5
1 5.5
1 0.5
1 3.5
1 2.5
1 4.5
1 4.5
1 4.5
0 6.0
1 2.5
1 5.0
1 0.0
1 5.0
1 6.5
1 5.0
0 6.0
1 4.5
1 5.5
0 1.0
1 7.5
0 6.0
0 5.0
0 1.0
1 5.0
0 6.5
1 7.0
1 4.5
0 0.0
1 8.5
0 3.5
0 7.5
1 3.5
1 6.0
1 1.5
1 9.0
1 3.5
0 3.5
1 4.0
1 6.5
1 7.5
0 6.0
1 5.0
1 5.5
0 3.5
0 7.5
1 1.0
1 6.5
1 6.5
0 6.5
1 7.0
0 3.5
1 1.5
0 4.0
0 7.5
0 4.5
0 0.0
0 3.5
0 5.5
0 5.0
0 4.5
0 2.5
0 7.5
0 7.0
0 0.0
0 4.5
0 3.0
0 1.5
0 3.5
0 2.5
0 5.5
0 8.0
0 1.0
0 5.0
0 4.5
0 3.0
0 3.0
0 8.0
0 2.5
0 7.0
0 0.0
0 1.0
0 3.5
0 5.5
0 5.5
1 0.5
1 7.5
1 9
1 9.5
0 8.5
0 7
1 8
1 10
1 7
1 8.5
1 9
1 9.5
1 4
1 6
1 8
1 5.5
0 9.5
1 7.5
1 7
1 7.5
1 8
1 7
1 7
1 6
1 10
1 2.5
1 9
1 8
0 6
1 8.5
1 6
1 9
1 8
1 8
1 9
1 5.5
1 5
1 7
1 5.5
1 9
1 2
1 8.5
1 9
1 8.5
0 9
0 7.5
1 10
1 9
0 7.5
0 6
0 10.5
0 8.5
1 8
1 10
0 10.5
0 6.5
0 9.5
0 8.5
0 7.5
0 5
0 8
0 10
0 7
1 7.5
1 7.5
0 9.5
1 6
1 10
0 7
1 3
0 6
0 7
1 10
0 7
0 3.5
0 8
0 10
0 5.5
0 6
0 6.5
0 6.5
0 8.5
0 4
0 9.5
0 8
0 8.5
1 5.5
0 7
0 9
0 8
1 10
0 8
1 6
0 8
1 5
0 9
1 4.5
0 8.5
0 7
0 9.5
0 8.5
0 7.5
1 7.5
1 5
0 7
1 8
1 5.5
0 8.5
1 7.5
1 9.5
0 7
0 8
1 8.5
0 3.5
1 6.5
1 6.5
1 10.5
0 8.5
1 8
0 10
1 10
1 9.5
1 9
1 10
0 7.5
1 4.5
1 4.5
1 0.5
0 6.5
1 4.5
1 5.5
0 5
1 6
0 4
0 8
0 10.5
1 8.5
0 6.5
0 8
1 8.5
1 5.5
1 7
1 5
1 3.5
1 5
0 9
0 8.5
1 5
0 9.5
0 3
1 1.5
0 6
0 0.5
0 6.5
0 7.5
0 4.5
0 8
0 9
0 7.5
0 8.5
0 7
0 9.5
0 6.5
0 9.5
0 6
0 8
0 9.5
0 8
1 8
0 9
0 5

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270512&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270512&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'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
Ex ~ course_bin
means6.299-0.286

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Ex  ~  course_bin \tabularnewline
means & 6.299 & -0.286 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270512&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Ex  ~  course_bin[/C][/ROW]
[ROW][C]means[/C][C]6.299[/C][C]-0.286[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270512&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
Ex ~ course_bin
means6.299-0.286






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
course_bin15.8325.8320.8920.346
Residuals2841857.2036.539 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
course_bin & 1 & 5.832 & 5.832 & 0.892 & 0.346 \tabularnewline
Residuals & 284 & 1857.203 & 6.539 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270512&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]course_bin[/C][C]1[/C][C]5.832[/C][C]5.832[/C][C]0.892[/C][C]0.346[/C][/ROW]
[ROW][C]Residuals[/C][C]284[/C][C]1857.203[/C][C]6.539[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270512&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270512&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)
course_bin15.8325.8320.8920.346
Residuals2841857.2036.539






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-0.286-0.8820.310.346

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -0.286 & -0.882 & 0.31 & 0.346 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270512&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]1-0[/C][C]-0.286[/C][C]-0.882[/C][C]0.31[/C][C]0.346[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270512&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270512&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
1-0-0.286-0.8820.310.346






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.0970.756
284 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.097 & 0.756 \tabularnewline
  & 284 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270512&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]1[/C][C]0.097[/C][C]0.756[/C][/ROW]
[ROW][C] [/C][C]284[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270512&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270512&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)
Group10.0970.756
284


Figures (Output of Computation)

Input Parameters & R Code

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