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Author's title

Author*Unverified author*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationSat, 03 Nov 2012 12:06:18 -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/2012/Nov/03/t1351958805s7ma8zmyocm29l2.htm/, Retrieved Thu, 18 Aug 2022 14:03:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185754, Retrieved Thu, 18 Aug 2022 14:03:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
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             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Exercise 1 ] [2012-11-01 13:20:10] [74be16979710d4c4e7c6647856088456]
-   PD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and of...] [2012-11-03 14:42:57] [74be16979710d4c4e7c6647856088456]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and of...] [2012-11-03 15:13:53] [74be16979710d4c4e7c6647856088456]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers warmth an...] [2012-11-03 15:48:22] [74be16979710d4c4e7c6647856088456]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers warmth an...] [2012-11-03 16:06:18] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1	NA
1	88
2	94
2	90
2	73
1	68
2	80
2	86
3	86
3	91
1	79
3	96
2	92
3	72
2	96
1	70
2	86
2	87
3	88
2	79
1	90
2	95
2	85
2	NA
2	90
3	115
3	84
2	79
1	94
2	97
2	86
3	111
2	87
3	98
3	87
1	68
1	88
3	82
3	111
2	75
1	94
1	95
1	80
2	95
2	68
1	94
1	88
3	84
2	NA
1	101
2	98
3	78
2	109
2	102
1	81
3	97
3	75
2	97
1	NA
1	101
3	101
2	95
2	95
2	NA
2	95
1	90
2	107
3	92
2	86
1	70
3	95
1	96
2	91
3	87
1	92
3	97
2	102
1	91
2	68
1	88
2	97
2	90
3	101
3	94
3	101
3	109
2	100
2	103
2	94
3	97
1	85
1	75
2	77
1	87
3	78
2	108
2	97
NA	105
2	106
2	107
2	95
3	107
2	115
2	101
3	85
3	90
3	115
2	95
2	97
1	112
3	97
2	77
2	90
2	94
2	103
2	77
1	98
2	90
2	111
1	77
1	88
2	75
3	92
1	78
3	106
1	80
2	87
1	92
3	NA
NA	111
1	86
3	85
2	90
3	101
2	94
2	86
3	86
2	90
3	75
2	86
1	91
2	97
1	91
1	70
1	98
1	96
2	95
2	100
2	95
1	97
3	97
3	92
3	115
2	88
1	87
2	100
3	98
2	102
2	NA
1	96




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=185754&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=185754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185754&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
WISCRY7V ~ MWARM30
means87.5614.7046.43920.439

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MWARM30 \tabularnewline
means & 87.561 & 4.704 & 6.439 & 20.439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185754&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]87.561[/C][C]4.704[/C][C]6.439[/C][C]20.439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185754&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
WISCRY7V ~ MWARM30
means87.5614.7046.43920.439







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM3031477.608492.5364.5530.004
Residuals14916119.333108.183

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 3 & 1477.608 & 492.536 & 4.553 & 0.004 \tabularnewline
Residuals & 149 & 16119.333 & 108.183 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185754&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]MWARM30[/C][C]3[/C][C]1477.608[/C][C]492.536[/C][C]4.553[/C][C]0.004[/C][/ROW]
[ROW][C]Residuals[/C][C]149[/C][C]16119.333[/C][C]108.183[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185754&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185754&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)
MWARM3031477.608492.5364.5530.004
Residuals14916119.333108.183







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-14.704-0.6410.0470.106
3-16.4390.50612.3720.028
NA-120.4390.86940.0090.037
3-21.735-3.5687.0390.83
NA-215.735-3.65335.1240.155
NA-314-5.55933.5590.25

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 4.704 & -0.64 & 10.047 & 0.106 \tabularnewline
3-1 & 6.439 & 0.506 & 12.372 & 0.028 \tabularnewline
NA-1 & 20.439 & 0.869 & 40.009 & 0.037 \tabularnewline
3-2 & 1.735 & -3.568 & 7.039 & 0.83 \tabularnewline
NA-2 & 15.735 & -3.653 & 35.124 & 0.155 \tabularnewline
NA-3 & 14 & -5.559 & 33.559 & 0.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185754&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]4.704[/C][C]-0.64[/C][C]10.047[/C][C]0.106[/C][/ROW]
[ROW][C]3-1[/C][C]6.439[/C][C]0.506[/C][C]12.372[/C][C]0.028[/C][/ROW]
[ROW][C]NA-1[/C][C]20.439[/C][C]0.869[/C][C]40.009[/C][C]0.037[/C][/ROW]
[ROW][C]3-2[/C][C]1.735[/C][C]-3.568[/C][C]7.039[/C][C]0.83[/C][/ROW]
[ROW][C]NA-2[/C][C]15.735[/C][C]-3.653[/C][C]35.124[/C][C]0.155[/C][/ROW]
[ROW][C]NA-3[/C][C]14[/C][C]-5.559[/C][C]33.559[/C][C]0.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185754&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185754&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
2-14.704-0.6410.0470.106
3-16.4390.50612.3720.028
NA-120.4390.86940.0090.037
3-21.735-3.5687.0390.83
NA-215.735-3.65335.1240.155
NA-314-5.55933.5590.25







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.8430.472
149

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.843 & 0.472 \tabularnewline
  & 149 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185754&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]3[/C][C]0.843[/C][C]0.472[/C][/ROW]
[ROW][C] [/C][C]149[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185754&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185754&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)
Group30.8430.472
149



Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; 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')