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Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 24 Nov 2011 07:53:12 -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/24/t1322139208xi20giu3kfl8wlw.htm/, Retrieved Thu, 28 Mar 2024 10:19:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146719, Retrieved Thu, 28 Mar 2024 10:19:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
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 PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-24 12:52:38] [09253b89c68efd7a460a267273a9d6e3]
-  M                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-24 12:53:12] [8e78b9caec05a843a8511780bd4770d3] [Current]
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Dataseries X:
1	6	88
3	8	94
3	8	90
3	7	73
1	5	68
2	7	80
3	8	86
3	9	86
2	9	91
1	3	79
1	9	96
3	7	92
3	9	72
3	8	96
1	6	70
3	7	86
3	8	87
3	9	88
2	7	79
2	6	90
1	8	95
1	7	85		
3	8	90
1	9	115
1	9	84
3	7	79
1	4	94
2	7	97
3	7	86
2	9	111
2	7	87
3	9	98
1	10	87
3	5	68
3	6	88
1	9	82
2	9	111
1	8	75
1	6	94
2	6	95
1	5	80
1	8	95
3	8	68
2	5	94
2	6	88
1	9	84		
1	4	101
1	8	98
2	9	78
3	7	109
3	7	102
3	6	81
3	9	97
2	9	75
2	8	97	
3	6	101
3	10	101
2	8	95
2	7	95
		
3	8	95
2	3	90
3	8	107
3	10	92
2	7	86
2	5	70
3	10	95
3	5	96
2	8	91
1	9	87
2	6	92
2	9	97
2	8	102
2	5	91
3	8	68
2	3	88
3	7	97
1	8	90
3	10	101
3	9	94
1	10	101
1	9	109
2	8	100
1	8	103
3	8	94
1	9	97
3	4	85
2	6	75
3	7	77
1	4	87
1	9	78
2	7	108
3	8	97
		
3	8	106
1	7	107
2	7	95
2	9	107
3	8	115
3	8	101
1	9	85
3	9	90
3	10	115
3	7	95
2	8	97
3	5	112
3	9	97
3	8	77
3	7	90
1	8	94
3	8	103
1	7	77
3	6	98
3	7	90
3	7	111
2	6	77
3	6	88
2	7	75
3	9	92
2	6	78
2	10	106
2	4	80
3	8	87
3	7	92
		
		
3	5	86
3	9	85
2	8	90
1	9	101
3	8	94
3	8	86
3	9	86
2	8	90
1	9	75
3	7	86
3	6	91
3	8	97
2	6	91
3	5	70
2	3	98
3	6	96
3	8	95
2	7	100
3	8	95
3	6	97
3	9	97
3	9	92
1	10	115
3	7	88
2	5	87
3	8	100
3	9	98
1	8	102
3	4	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.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=146719&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]'AstonUniversity' @ aston.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=146719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146719&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'AstonUniversity' @ aston.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
MWARM30 ~ MOMAGE
means7.556-0.6980.029

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MWARM30  ~  MOMAGE \tabularnewline
means & 7.556 & -0.698 & 0.029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146719&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MWARM30  ~  MOMAGE[/C][/ROW]
[ROW][C]means[/C][C]7.556[/C][C]-0.698[/C][C]0.029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146719&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
MWARM30 ~ MOMAGE
means7.556-0.6980.029







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MOMAGE215.8097.9043.0130.052
Residuals152398.7332.623

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MOMAGE & 2 & 15.809 & 7.904 & 3.013 & 0.052 \tabularnewline
Residuals & 152 & 398.733 & 2.623 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146719&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]MOMAGE[/C][C]2[/C][C]15.809[/C][C]7.904[/C][C]3.013[/C][C]0.052[/C][/ROW]
[ROW][C]Residuals[/C][C]152[/C][C]398.733[/C][C]2.623[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146719&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)
MOMAGE215.8097.9043.0130.052
Residuals152398.7332.623







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-1-0.698-1.5690.1720.143
3-10.029-0.7450.8030.996
3-20.727-0.0081.4630.053

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.698 & -1.569 & 0.172 & 0.143 \tabularnewline
3-1 & 0.029 & -0.745 & 0.803 & 0.996 \tabularnewline
3-2 & 0.727 & -0.008 & 1.463 & 0.053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146719&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]-0.698[/C][C]-1.569[/C][C]0.172[/C][C]0.143[/C][/ROW]
[ROW][C]3-1[/C][C]0.029[/C][C]-0.745[/C][C]0.803[/C][C]0.996[/C][/ROW]
[ROW][C]3-2[/C][C]0.727[/C][C]-0.008[/C][C]1.463[/C][C]0.053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146719&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
2-1-0.698-1.5690.1720.143
3-10.029-0.7450.8030.996
3-20.727-0.0081.4630.053







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group21.9780.142
152

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.978 & 0.142 \tabularnewline
  & 152 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146719&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]1.978[/C][C]0.142[/C][/ROW]
[ROW][C] [/C][C]152[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146719&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146719&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)
Group21.9780.142
152



Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = TRUE ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')