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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, 28 Nov 2011 09:31:21 -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/2011/Nov/28/t1322490701yl7t4j0lfckexqv.htm/, Retrieved Thu, 28 Mar 2024 13:47:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147754, Retrieved Thu, 28 Mar 2024 13:47:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WORKSHOP 8- IQ] [2011-11-28 14:27:08] [db177c22332ffa2a0a999e2f71898de2]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WORKSHOP 8- IQ] [2011-11-28 14:31:21] [68e47018849be3915773eb95b1368c99] [Current]
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Dataseries X:
1	2
3	2
3	3
3	2
1	1
2	2
3	2
3	2
2	3
1	1
1	3
3	2
3	1
3	2
1	2
3	2
3	1
3	3
2	2
2	1
1	1
1	1
3	2
1	3
1	2
3	2
1	2
2	2
3	2
2	3
2	2
3	2
1	2
3	1
3	2
1	2
2	3
1	1
1	2
2	1
1	2
1	3
3	2
2	2
2	2
1	1
1	2
1	2
2	1
3	3
3	1
3	1
3	1
2	2
2	2
3	1
3	1
2	2
2	2
3	2
2	2
3	3
3	2
2	1
2	1
3	2
3	1
2	2
1	3
2	3
2	3
2	3
2	1
3	2
2	1
3	2
1	1
3	2
3	2
1	3
1	3
2	2
1	2
3	2
1	2
3	2
2	2
3	1
1	1
1	1
2	3
3	2
3	2
1	2
2	1
2	3
3	2
3	2
1	1
3	2
3	3
3	2
2	1
3	1
3	1
3	1
3	2
1	2
3	3
1	2
3	2
3	2
3	3
2	1
3	3
2	1
3	2
2	2
2	2
2	1
3	2
3	1
3	2
3	2
2	1
1	3
3	2
3	1
3	1
2	1
1	1
3	2
3	3
3	2
2	2
3	1
2	2
3	1
3	1
2	2
3	1
3	2
3	1
3	3
1	3
3	3
2	2
3	2
3	2
1	1
3	1





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=147754&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=147754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147754&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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







ANOVA Model
MOMAGE ~ MCVB1Q
means2.2080.134-0.097

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MOMAGE  ~  MCVB1Q \tabularnewline
means & 2.208 & 0.134 & -0.097 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147754&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MOMAGE  ~  MCVB1Q[/C][/ROW]
[ROW][C]means[/C][C]2.208[/C][C]0.134[/C][C]-0.097[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147754&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
MOMAGE ~ MCVB1Q
means2.2080.134-0.097







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MCVB1Q21.2390.6190.9380.394
Residuals14897.6890.66

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MCVB1Q & 2 & 1.239 & 0.619 & 0.938 & 0.394 \tabularnewline
Residuals & 148 & 97.689 & 0.66 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147754&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]MCVB1Q[/C][C]2[/C][C]1.239[/C][C]0.619[/C][C]0.938[/C][C]0.394[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]97.689[/C][C]0.66[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147754&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147754&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)
MCVB1Q21.2390.6190.9380.394
Residuals14897.6890.66







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.134-0.2210.4880.646
3-1-0.097-0.560.3650.873
3-2-0.231-0.6620.20.415

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.134 & -0.221 & 0.488 & 0.646 \tabularnewline
3-1 & -0.097 & -0.56 & 0.365 & 0.873 \tabularnewline
3-2 & -0.231 & -0.662 & 0.2 & 0.415 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147754&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]2-1[/C][C]0.134[/C][C]-0.221[/C][C]0.488[/C][C]0.646[/C][/ROW]
[ROW][C]3-1[/C][C]-0.097[/C][C]-0.56[/C][C]0.365[/C][C]0.873[/C][/ROW]
[ROW][C]3-2[/C][C]-0.231[/C][C]-0.662[/C][C]0.2[/C][C]0.415[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147754&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147754&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
2-10.134-0.2210.4880.646
3-1-0.097-0.560.3650.873
3-2-0.231-0.6620.20.415







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.1060.899
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.106 & 0.899 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147754&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]2[/C][C]0.106[/C][C]0.899[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147754&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147754&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)
Group20.1060.899
148



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){
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')