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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 computationThu, 27 Oct 2011 15:10:19 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/27/t1319742696pf8iirrn21dtqt0.htm/, Retrieved Thu, 16 May 2024 22:28:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=137492, Retrieved Thu, 16 May 2024 22:28:12 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

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)] [] [2011-10-27 19:10:19] [694c30abd2a3b2ee5cb46fc74cb5bfb9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	1	0
1	0	1	1
0	3	0	1
0	-1	0	0
0	3	0	1
0	-1	-1	-1
0	-1	0	-0.5
0	0	1	0
1	4	1	2
1	0	0	0
0	-1	-1	0
0	3	0	1
0	4	0	0.5
1	0	1	2
0	0	0	1
1	0	1	2
0	4	NA	NA
1	0	0	0
1	2	1	0
1	0	1	0.5
1	4	NA	NA
0	4	0	2
0	0	NA	NA
1	0	1	0
0	3	0	1
0	-1	0	0
-1	-1	0	-1
0	2	1	2
1	0	0	1
1	0	1	2
0	0	0	0
0	3	0	0
0	3	0	1

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'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137492&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137492&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137492&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'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
post2-pre ~ post4-pre
means-101.27332.8752.6673.667

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post2-pre  ~  post4-pre \tabularnewline
means & -1 & 0 & 1.273 & 3 & 2.875 & 2.667 & 3.667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137492&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post2-pre  ~  post4-pre[/C][/ROW]
[ROW][C]means[/C][C]-1[/C][C]0[/C][C]1.273[/C][C]3[/C][C]2.875[/C][C]2.667[/C][C]3.667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137492&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137492&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 ~ post4-pre
means-101.27332.8752.6673.667






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
post4-pre636.4586.0762.2230.073
Residuals2671.0572.733 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post4-pre & 6 & 36.458 & 6.076 & 2.223 & 0.073 \tabularnewline
Residuals & 26 & 71.057 & 2.733 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137492&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]post4-pre[/C][C]6[/C][C]36.458[/C][C]6.076[/C][C]2.223[/C][C]0.073[/C][/ROW]
[ROW][C]Residuals[/C][C]26[/C][C]71.057[/C][C]2.733[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137492&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137492&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)
post4-pre636.4586.0762.2230.073
Residuals2671.0572.733






Tukey Honest Significant Difference Comparisons
difflwruprp adj
-1--0.50-6.4596.4591
0--0.51.273-4.2366.7810.989
0.5--0.53-3.4599.4590.753
1--0.52.875-2.7198.4690.659
2--0.52.667-3.038.3630.746
NA--0.53.667-2.4239.7560.485
0--11.273-2.7815.3270.949
0.5--13-2.2748.2740.551
1--12.875-1.2947.0440.329
2--12.667-1.6396.9730.453
NA--13.667-1.1488.4810.227
0.5-01.727-2.3275.7810.818
1-01.602-0.8484.0530.39
2-01.394-1.2834.070.646
NA-02.394-1.0415.8290.318
1-0.5-0.125-4.2944.0441
2-0.5-0.333-4.6393.9731
NA-0.50.667-4.1485.4810.999
2-1-0.208-3.0562.641
NA-10.792-2.7794.3620.991
NA-21-2.7294.7290.976

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
-1--0.5 & 0 & -6.459 & 6.459 & 1 \tabularnewline
0--0.5 & 1.273 & -4.236 & 6.781 & 0.989 \tabularnewline
0.5--0.5 & 3 & -3.459 & 9.459 & 0.753 \tabularnewline
1--0.5 & 2.875 & -2.719 & 8.469 & 0.659 \tabularnewline
2--0.5 & 2.667 & -3.03 & 8.363 & 0.746 \tabularnewline
NA--0.5 & 3.667 & -2.423 & 9.756 & 0.485 \tabularnewline
0--1 & 1.273 & -2.781 & 5.327 & 0.949 \tabularnewline
0.5--1 & 3 & -2.274 & 8.274 & 0.551 \tabularnewline
1--1 & 2.875 & -1.294 & 7.044 & 0.329 \tabularnewline
2--1 & 2.667 & -1.639 & 6.973 & 0.453 \tabularnewline
NA--1 & 3.667 & -1.148 & 8.481 & 0.227 \tabularnewline
0.5-0 & 1.727 & -2.327 & 5.781 & 0.818 \tabularnewline
1-0 & 1.602 & -0.848 & 4.053 & 0.39 \tabularnewline
2-0 & 1.394 & -1.283 & 4.07 & 0.646 \tabularnewline
NA-0 & 2.394 & -1.041 & 5.829 & 0.318 \tabularnewline
1-0.5 & -0.125 & -4.294 & 4.044 & 1 \tabularnewline
2-0.5 & -0.333 & -4.639 & 3.973 & 1 \tabularnewline
NA-0.5 & 0.667 & -4.148 & 5.481 & 0.999 \tabularnewline
2-1 & -0.208 & -3.056 & 2.64 & 1 \tabularnewline
NA-1 & 0.792 & -2.779 & 4.362 & 0.991 \tabularnewline
NA-2 & 1 & -2.729 & 4.729 & 0.976 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137492&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--0.5[/C][C]0[/C][C]-6.459[/C][C]6.459[/C][C]1[/C][/ROW]
[ROW][C]0--0.5[/C][C]1.273[/C][C]-4.236[/C][C]6.781[/C][C]0.989[/C][/ROW]
[ROW][C]0.5--0.5[/C][C]3[/C][C]-3.459[/C][C]9.459[/C][C]0.753[/C][/ROW]
[ROW][C]1--0.5[/C][C]2.875[/C][C]-2.719[/C][C]8.469[/C][C]0.659[/C][/ROW]
[ROW][C]2--0.5[/C][C]2.667[/C][C]-3.03[/C][C]8.363[/C][C]0.746[/C][/ROW]
[ROW][C]NA--0.5[/C][C]3.667[/C][C]-2.423[/C][C]9.756[/C][C]0.485[/C][/ROW]
[ROW][C]0--1[/C][C]1.273[/C][C]-2.781[/C][C]5.327[/C][C]0.949[/C][/ROW]
[ROW][C]0.5--1[/C][C]3[/C][C]-2.274[/C][C]8.274[/C][C]0.551[/C][/ROW]
[ROW][C]1--1[/C][C]2.875[/C][C]-1.294[/C][C]7.044[/C][C]0.329[/C][/ROW]
[ROW][C]2--1[/C][C]2.667[/C][C]-1.639[/C][C]6.973[/C][C]0.453[/C][/ROW]
[ROW][C]NA--1[/C][C]3.667[/C][C]-1.148[/C][C]8.481[/C][C]0.227[/C][/ROW]
[ROW][C]0.5-0[/C][C]1.727[/C][C]-2.327[/C][C]5.781[/C][C]0.818[/C][/ROW]
[ROW][C]1-0[/C][C]1.602[/C][C]-0.848[/C][C]4.053[/C][C]0.39[/C][/ROW]
[ROW][C]2-0[/C][C]1.394[/C][C]-1.283[/C][C]4.07[/C][C]0.646[/C][/ROW]
[ROW][C]NA-0[/C][C]2.394[/C][C]-1.041[/C][C]5.829[/C][C]0.318[/C][/ROW]
[ROW][C]1-0.5[/C][C]-0.125[/C][C]-4.294[/C][C]4.044[/C][C]1[/C][/ROW]
[ROW][C]2-0.5[/C][C]-0.333[/C][C]-4.639[/C][C]3.973[/C][C]1[/C][/ROW]
[ROW][C]NA-0.5[/C][C]0.667[/C][C]-4.148[/C][C]5.481[/C][C]0.999[/C][/ROW]
[ROW][C]2-1[/C][C]-0.208[/C][C]-3.056[/C][C]2.64[/C][C]1[/C][/ROW]
[ROW][C]NA-1[/C][C]0.792[/C][C]-2.779[/C][C]4.362[/C][C]0.991[/C][/ROW]
[ROW][C]NA-2[/C][C]1[/C][C]-2.729[/C][C]4.729[/C][C]0.976[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137492&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137492&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--0.50-6.4596.4591
0--0.51.273-4.2366.7810.989
0.5--0.53-3.4599.4590.753
1--0.52.875-2.7198.4690.659
2--0.52.667-3.038.3630.746
NA--0.53.667-2.4239.7560.485
0--11.273-2.7815.3270.949
0.5--13-2.2748.2740.551
1--12.875-1.2947.0440.329
2--12.667-1.6396.9730.453
NA--13.667-1.1488.4810.227
0.5-01.727-2.3275.7810.818
1-01.602-0.8484.0530.39
2-01.394-1.2834.070.646
NA-02.394-1.0415.8290.318
1-0.5-0.125-4.2944.0441
2-0.5-0.333-4.6393.9731
NA-0.50.667-4.1485.4810.999
2-1-0.208-3.0562.641
NA-10.792-2.7794.3620.991
NA-21-2.7294.7290.976






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group60.8370.552
26 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 6 & 0.837 & 0.552 \tabularnewline
  & 26 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137492&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]0.837[/C][C]0.552[/C][/ROW]
[ROW][C] [/C][C]26[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137492&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137492&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)
Group60.8370.552
26


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 4 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 4 ; 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')