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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 computationMon, 17 Dec 2012 08:09:39 -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/17/t1355749809wyjud3gelnq5up8.htm/, Retrieved Fri, 29 Mar 2024 07:17:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200840, Retrieved Fri, 29 Mar 2024 07:17:12 +0000
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User-defined keywords
Estimated Impact68
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)] [] [2010-11-01 13:37:53] [b98453cac15ba1066b407e146608df68]
- R P     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [RFC - ANOVA] [2012-12-17 13:09:39] [7ac586d7aaad1f98cbd1d1bd98b37cf0] [Current]
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Dataseries X:
1	1	4	0	2	'T'	0	3	-1	1	4
1	1	0	0	2	'T'	0	-1	-1	1	0
0	1	4	1	1.5	'T'	1	4	1	1.5	5
0	0	0	0	0	'T'	0	0	0	0	0
1	1	0	1	1	'T'	0	-1	0	0	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	0	1	2	'T'	0	-1	0	1	0
0	1	0	1	1	'T'	1	0	1	1	1
0	1	4	1	2	'T'	1	4	1	2	5
1	1	1	0	2	'T'	0	0	-1	1	1
0	0	4	0	2	'T'	0	4	0	2	4
0	1	0	1	0	'T'	1	0	1	0	1
0	1	2	1	0	'T'	1	2	1	0	3
0	1	0	0	2	'T'	1	0	0	2	1
0	0	0	NA	NA	'T'	0	0	NA	NA	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	1	0	2	'T'	0	0	-1	1	1
1	1	0	1	0.5	'T'	0	-1	0	-0.5	0
0	1	0	1	2	'T'	1	0	1	2	1
0	0	2	1	0	'T'	0	2	1	0	2
1	1	2	1	2	'T'	0	1	0	1	2
1	1	1	0	0	'T'	0	0	-1	-1	1
0	0	2	NA	NA	'T'	0	2	NA	NA	2
1	0	0	NA	NA	'T'	-1	-1	NA	NA	-1
1	1	3	1	2	'T'	0	2	0	1	3
1	0	0	1	0	'T'	-1	-1	0	-1	-1
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
0	0	0	NA	NA	'T'	0	0	NA	NA	0
0	0	1	0	2	'T'	0	1	0	2	1
1	1	0	1	1	'T'	0	-1	0	0	0
1	0	0	0	0.5	'T'	-1	-1	-1	-0.5	-1
1	1	4	0	2	'T'	0	3	-1	1	4
0	0	0	1	0.5	'T'	0	0	1	0.5	0
0	0	1	NA	NA	'T'	0	1	NA	NA	1
0	0	0	1	0.5	'T'	0	0	1	0.5	0
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
1	1	4	0	2	'T'	0	3	-1	1	4
0	1	1	1	0	'E'	1	1	1	0	2
0	1	0	1	1	'E'	1	0	1	1	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	0	0	'E'	0	-1	-1	-1	0
1	1	0	1	0.5	'E'	0	-1	0	-0.5	0
0	0	0	1	0	'E'	0	0	1	0	0
0	1	4	1	2	'E'	1	4	1	2	5
0	1	0	0	0	'E'	1	0	0	0	1
1	1	0	0	1	'E'	0	-1	-1	0	0
1	1	4	1	2	'E'	0	3	0	1	4
0	0	4	0	0.5	'E'	0	4	0	0.5	4
0	1	0	1	2	'E'	1	0	1	2	1
1	1	1	1	2	'E'	0	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	4	NA	NA	'E'	0	4	NA	NA	4
0	1	0	0	0	'E'	1	0	0	0	1
0	1	2	1	0	'E'	1	2	1	0	3
0	1	0	1	0.5	'E'	1	0	1	0.5	1
0	1	4	NA	NA	'E'	1	4	NA	NA	5
0	0	4	0	2	'E'	0	4	0	2	4
0	0	0	NA	NA	'E'	0	0	NA	NA	0
0	1	0	1	0	'E'	1	0	1	0	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	0	0	1	0	'E'	-1	-1	0	-1	-1
0	0	2	1	2	'E'	0	2	1	2	2
0	1	0	0	1	'E'	1	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	0	0	0	'E'	0	0	0	0	0
1	1	4	1	1	'E'	0	3	0	0	4
1	1	4	1	2	'E'	0	3	0	1	4
0	1	2	0	0	'S'	1	2	0	0	3
0	1	0	0	0	'S'	1	0	0	0	1
0	1	0	0	0	'S'	1	0	0	0	1
0	1	4	0	0	'S'	1	4	0	0	5
1	1	0	1	2	'S'	0	-1	0	1	0
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	1	1	2	'S'	0	1	1	2	1
1	1	2	1	2	'S'	0	1	0	1	2
1	0	0	1	2	'S'	-1	-1	0	1	-1
1	1	2	1	2	'S'	0	1	0	1	2
0	0	0	1	2	'S'	0	0	1	2	0
0	0	4	1	2	'S'	0	4	1	2	4
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	NA	NA	'S'	-1	-1	NA	NA	-1
1	1	4	1	2	'S'	0	3	0	1	4
0	0	2	1	2	'S'	0	2	1	2	2
0	0	2	NA	NA	'S'	0	2	NA	NA	2
1	1	0	0	0	'S'	0	-1	-1	-1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	NA	NA	'S'	0	3	NA	NA	4
0	1	0	1	2	'S'	1	0	1	2	1
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	1	2	'S'	0	3	0	1	4
1	1	4	1	2	'S'	0	3	0	1	4
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	0	0	0	'S'	0	0	0	0	0
1	1	2	0	0	'S'	0	1	-1	-1	2
0	0	1	1	2	'S'	0	1	1	2	1
0	0	0	0	0	'S'	0	0	0	0	0
0	0	2	1	2	'S'	0	2	1	2	2
0	1	1	0	0	'S'	1	1	0	0	2




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=200840&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=200840&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200840&T=0

As an alternative you can also use a 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
pre ~ post2-pre
means1-0.879-0.6-0.90-1

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
pre  ~  post2-pre \tabularnewline
means & 1 & -0.879 & -0.6 & -0.9 & 0 & -1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200840&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]pre  ~  post2-pre[/C][/ROW]
[ROW][C]means[/C][C]1[/C][C]-0.879[/C][C]-0.6[/C][C]-0.9[/C][C]0[/C][C]-1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200840&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200840&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
pre ~ post2-pre
means1-0.879-0.6-0.90-1







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
post2-pre519.3183.86456.1250
Residuals996.8150.069

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post2-pre & 5 & 19.318 & 3.864 & 56.125 & 0 \tabularnewline
Residuals & 99 & 6.815 & 0.069 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200840&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]post2-pre[/C][C]5[/C][C]19.318[/C][C]3.864[/C][C]56.125[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]99[/C][C]6.815[/C][C]0.069[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200840&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200840&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
post2-pre519.3183.86456.1250
Residuals996.8150.069







Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--1-0.879-1.077-0.6810
1--1-0.6-0.882-0.3180
2--1-0.9-1.182-0.6180
3--10-0.2570.2571
4--1-1-1.265-0.7350
1-00.2790.0040.5540.045
2-0-0.021-0.2960.2541
3-00.8790.6291.1280
4-0-0.121-0.3780.1360.744
2-1-0.3-0.6410.0410.118
3-10.60.2790.9210
4-1-0.4-0.726-0.0740.007
3-20.90.5791.2210
4-2-0.1-0.4260.2260.948
4-3-1-1.305-0.6950

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & -0.879 & -1.077 & -0.681 & 0 \tabularnewline
1--1 & -0.6 & -0.882 & -0.318 & 0 \tabularnewline
2--1 & -0.9 & -1.182 & -0.618 & 0 \tabularnewline
3--1 & 0 & -0.257 & 0.257 & 1 \tabularnewline
4--1 & -1 & -1.265 & -0.735 & 0 \tabularnewline
1-0 & 0.279 & 0.004 & 0.554 & 0.045 \tabularnewline
2-0 & -0.021 & -0.296 & 0.254 & 1 \tabularnewline
3-0 & 0.879 & 0.629 & 1.128 & 0 \tabularnewline
4-0 & -0.121 & -0.378 & 0.136 & 0.744 \tabularnewline
2-1 & -0.3 & -0.641 & 0.041 & 0.118 \tabularnewline
3-1 & 0.6 & 0.279 & 0.921 & 0 \tabularnewline
4-1 & -0.4 & -0.726 & -0.074 & 0.007 \tabularnewline
3-2 & 0.9 & 0.579 & 1.221 & 0 \tabularnewline
4-2 & -0.1 & -0.426 & 0.226 & 0.948 \tabularnewline
4-3 & -1 & -1.305 & -0.695 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200840&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]-0.879[/C][C]-1.077[/C][C]-0.681[/C][C]0[/C][/ROW]
[ROW][C]1--1[/C][C]-0.6[/C][C]-0.882[/C][C]-0.318[/C][C]0[/C][/ROW]
[ROW][C]2--1[/C][C]-0.9[/C][C]-1.182[/C][C]-0.618[/C][C]0[/C][/ROW]
[ROW][C]3--1[/C][C]0[/C][C]-0.257[/C][C]0.257[/C][C]1[/C][/ROW]
[ROW][C]4--1[/C][C]-1[/C][C]-1.265[/C][C]-0.735[/C][C]0[/C][/ROW]
[ROW][C]1-0[/C][C]0.279[/C][C]0.004[/C][C]0.554[/C][C]0.045[/C][/ROW]
[ROW][C]2-0[/C][C]-0.021[/C][C]-0.296[/C][C]0.254[/C][C]1[/C][/ROW]
[ROW][C]3-0[/C][C]0.879[/C][C]0.629[/C][C]1.128[/C][C]0[/C][/ROW]
[ROW][C]4-0[/C][C]-0.121[/C][C]-0.378[/C][C]0.136[/C][C]0.744[/C][/ROW]
[ROW][C]2-1[/C][C]-0.3[/C][C]-0.641[/C][C]0.041[/C][C]0.118[/C][/ROW]
[ROW][C]3-1[/C][C]0.6[/C][C]0.279[/C][C]0.921[/C][C]0[/C][/ROW]
[ROW][C]4-1[/C][C]-0.4[/C][C]-0.726[/C][C]-0.074[/C][C]0.007[/C][/ROW]
[ROW][C]3-2[/C][C]0.9[/C][C]0.579[/C][C]1.221[/C][C]0[/C][/ROW]
[ROW][C]4-2[/C][C]-0.1[/C][C]-0.426[/C][C]0.226[/C][C]0.948[/C][/ROW]
[ROW][C]4-3[/C][C]-1[/C][C]-1.305[/C][C]-0.695[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200840&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200840&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--1-0.879-1.077-0.6810
1--1-0.6-0.882-0.3180
2--1-0.9-1.182-0.6180
3--10-0.2570.2571
4--1-1-1.265-0.7350
1-00.2790.0040.5540.045
2-0-0.021-0.2960.2541
3-00.8790.6291.1280
4-0-0.121-0.3780.1360.744
2-1-0.3-0.6410.0410.118
3-10.60.2790.9210
4-1-0.4-0.726-0.0740.007
3-20.90.5791.2210
4-2-0.1-0.4260.2260.948
4-3-1-1.305-0.6950







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group54.1060.002
99

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 4.106 & 0.002 \tabularnewline
  & 99 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200840&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]5[/C][C]4.106[/C][C]0.002[/C][/ROW]
[ROW][C] [/C][C]99[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200840&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200840&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group54.1060.002
99



Parameters (Session):
par1 = 1 ; par2 = 8 ; par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 8 ; 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')