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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 computationSat, 15 Dec 2012 17:09:51 -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/2012/Dec/15/t13556094576wh8hw0kjkt44ap.htm/, Retrieved Tue, 30 Apr 2024 19:37:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200155, Retrieved Tue, 30 Apr 2024 19:37:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

Tree of Dependent Computations

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-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [anova1] [2012-12-15 22:09:51] [081b45eff66f9ee50ac0b17603ac2bbc] [Current]
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Dataset

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

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200155&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200155&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200155&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
post2-pre ~ Tot-pre
means-10.4061.1672.534.355

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post2-pre  ~  Tot-pre \tabularnewline
means & -1 & 0.406 & 1.167 & 2.5 & 3 & 4.35 & 5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200155&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post2-pre  ~  Tot-pre[/C][/ROW]
[ROW][C]means[/C][C]-1[/C][C]0.406[/C][C]1.167[/C][C]2.5[/C][C]3[/C][C]4.35[/C][C]5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200155&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200155&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
post2-pre ~ Tot-pre
means-10.4061.1672.534.355






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Tot-pre6290.25548.376254.8550
Residuals9818.6020.19 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Tot-pre & 6 & 290.255 & 48.376 & 254.855 & 0 \tabularnewline
Residuals & 98 & 18.602 & 0.19 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200155&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]Tot-pre[/C][C]6[/C][C]290.255[/C][C]48.376[/C][C]254.855[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]98[/C][C]18.602[/C][C]0.19[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200155&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200155&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)
Tot-pre6290.25548.376254.8550
Residuals9818.6020.19






Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--10.406-0.1120.9250.227
1--11.1670.6311.7020
2--12.51.9013.0990
3--132.1973.8030
4--14.353.8014.8990
5--154.2525.7480
1-00.760.4061.1150
2-02.0941.652.5380
3-02.5941.8983.2890
4-03.9443.574.3180
5-04.5943.9635.2240
2-11.3330.871.7970
3-11.8331.1252.5420
4-13.1832.7863.580
5-13.8333.1894.4780
3-20.5-0.2571.2570.429
4-21.851.3712.3290
5-22.51.8023.1980
4-31.350.6322.0680
5-321.122.880
5-40.65-0.0061.3060.054

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & 0.406 & -0.112 & 0.925 & 0.227 \tabularnewline
1--1 & 1.167 & 0.631 & 1.702 & 0 \tabularnewline
2--1 & 2.5 & 1.901 & 3.099 & 0 \tabularnewline
3--1 & 3 & 2.197 & 3.803 & 0 \tabularnewline
4--1 & 4.35 & 3.801 & 4.899 & 0 \tabularnewline
5--1 & 5 & 4.252 & 5.748 & 0 \tabularnewline
1-0 & 0.76 & 0.406 & 1.115 & 0 \tabularnewline
2-0 & 2.094 & 1.65 & 2.538 & 0 \tabularnewline
3-0 & 2.594 & 1.898 & 3.289 & 0 \tabularnewline
4-0 & 3.944 & 3.57 & 4.318 & 0 \tabularnewline
5-0 & 4.594 & 3.963 & 5.224 & 0 \tabularnewline
2-1 & 1.333 & 0.87 & 1.797 & 0 \tabularnewline
3-1 & 1.833 & 1.125 & 2.542 & 0 \tabularnewline
4-1 & 3.183 & 2.786 & 3.58 & 0 \tabularnewline
5-1 & 3.833 & 3.189 & 4.478 & 0 \tabularnewline
3-2 & 0.5 & -0.257 & 1.257 & 0.429 \tabularnewline
4-2 & 1.85 & 1.371 & 2.329 & 0 \tabularnewline
5-2 & 2.5 & 1.802 & 3.198 & 0 \tabularnewline
4-3 & 1.35 & 0.632 & 2.068 & 0 \tabularnewline
5-3 & 2 & 1.12 & 2.88 & 0 \tabularnewline
5-4 & 0.65 & -0.006 & 1.306 & 0.054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200155&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]0.406[/C][C]-0.112[/C][C]0.925[/C][C]0.227[/C][/ROW]
[ROW][C]1--1[/C][C]1.167[/C][C]0.631[/C][C]1.702[/C][C]0[/C][/ROW]
[ROW][C]2--1[/C][C]2.5[/C][C]1.901[/C][C]3.099[/C][C]0[/C][/ROW]
[ROW][C]3--1[/C][C]3[/C][C]2.197[/C][C]3.803[/C][C]0[/C][/ROW]
[ROW][C]4--1[/C][C]4.35[/C][C]3.801[/C][C]4.899[/C][C]0[/C][/ROW]
[ROW][C]5--1[/C][C]5[/C][C]4.252[/C][C]5.748[/C][C]0[/C][/ROW]
[ROW][C]1-0[/C][C]0.76[/C][C]0.406[/C][C]1.115[/C][C]0[/C][/ROW]
[ROW][C]2-0[/C][C]2.094[/C][C]1.65[/C][C]2.538[/C][C]0[/C][/ROW]
[ROW][C]3-0[/C][C]2.594[/C][C]1.898[/C][C]3.289[/C][C]0[/C][/ROW]
[ROW][C]4-0[/C][C]3.944[/C][C]3.57[/C][C]4.318[/C][C]0[/C][/ROW]
[ROW][C]5-0[/C][C]4.594[/C][C]3.963[/C][C]5.224[/C][C]0[/C][/ROW]
[ROW][C]2-1[/C][C]1.333[/C][C]0.87[/C][C]1.797[/C][C]0[/C][/ROW]
[ROW][C]3-1[/C][C]1.833[/C][C]1.125[/C][C]2.542[/C][C]0[/C][/ROW]
[ROW][C]4-1[/C][C]3.183[/C][C]2.786[/C][C]3.58[/C][C]0[/C][/ROW]
[ROW][C]5-1[/C][C]3.833[/C][C]3.189[/C][C]4.478[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]0.5[/C][C]-0.257[/C][C]1.257[/C][C]0.429[/C][/ROW]
[ROW][C]4-2[/C][C]1.85[/C][C]1.371[/C][C]2.329[/C][C]0[/C][/ROW]
[ROW][C]5-2[/C][C]2.5[/C][C]1.802[/C][C]3.198[/C][C]0[/C][/ROW]
[ROW][C]4-3[/C][C]1.35[/C][C]0.632[/C][C]2.068[/C][C]0[/C][/ROW]
[ROW][C]5-3[/C][C]2[/C][C]1.12[/C][C]2.88[/C][C]0[/C][/ROW]
[ROW][C]5-4[/C][C]0.65[/C][C]-0.006[/C][C]1.306[/C][C]0.054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200155&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200155&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--10.406-0.1120.9250.227
1--11.1670.6311.7020
2--12.51.9013.0990
3--132.1973.8030
4--14.353.8014.8990
5--154.2525.7480
1-00.760.4061.1150
2-02.0941.652.5380
3-02.5941.8983.2890
4-03.9443.574.3180
5-04.5943.9635.2240
2-11.3330.871.7970
3-11.8331.1252.5420
4-13.1832.7863.580
5-13.8333.1894.4780
3-20.5-0.2571.2570.429
4-21.851.3712.3290
5-22.51.8023.1980
4-31.350.6322.0680
5-321.122.880
5-40.65-0.0061.3060.054






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group62.9590.011
98 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 6 & 2.959 & 0.011 \tabularnewline
  & 98 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200155&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]6[/C][C]2.959[/C][C]0.011[/C][/ROW]
[ROW][C] [/C][C]98[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200155&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200155&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)
Group62.9590.011
98


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = 7 ; par3 = TRUE ;
Parameters (R input):
par1 = 6 ; par2 = 7 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'TRUE'
par2 <- '7'
par1 <- '6'
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')