Free Statistics

of Irreproducible Research!

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 computationFri, 02 Nov 2012 13:21:59 -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/02/t1351877003jvsk1yi42r0v3py.htm/, Retrieved Mon, 27 Jun 2022 06:16:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185655, Retrieved Mon, 27 Jun 2022 06:16:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
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)] [ANOVA - MOMAGE, M...] [2012-11-02 17:21:59] [9c9871bec7fca0615213f8a921560794] [Current]
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Dataseries X:
1	36	88
3	56	94
3	48	90
3	32	73
1	44	68
2	39	80
3	34	86
3	41	86
2	50	91
1	39	79
1	62	96
3	52	92
3	37	72
3	50	96
1	41	70
3	55	86
3	41	87
3	56	88
2	39	79
2	52	90
1	46	95
1	44	85
3	41	90
1	50	115
1	50	84
3	44	79
1	52	94
2	54	97
3	44	86
2	52	111
2	37	87
3	52	98
1	50	87
3	36	68
3	50	88
1	52	82
2	55	111
1	31	75
1	36	94
2	49	95
1	42	80
1	37	95
3	41	68
2	30	94
2	52	88
1	30	84
1	44	101
1	66	98
2	48	78
3	43	109
3	57	102
3	46	81
3	54	97
2	48	75
2	48	97
3	62	101
3	58	101
2	58	95
2	62	95
3	46	95
2	34	90
3	66	107
3	52	92
2	55	86
2	55	70
3	57	95
3	56	96
2	55	91
1	56	87
2	54	92
2	55	97
2	46	102
2	52	91
3	32	68
2	44	88
3	46	97
1	59	90
3	46	101
3	46	94
1	54	101
1	66	109
2	56	100
1	59	103
3	57	94
1	52	97
3	48	85
2	44	75
3	41	77
1	50	87
1	48	78
2	48	108
3	59	97
3	46	106
1	54	107
2	55	95
2	54	107
3	59	115
3	44	101
1	54	85
3	52	90
3	66	115
3	44	95
2	57	97
3	39	112
3	60	97
3	45	77
3	41	90
1	50	94
3	39	103
1	43	77
3	48	98
3	37	90
3	58	111
2	46	77
3	43	88
2	44	75
3	34	92
2	30	78
2	50	106
2	39	80
3	37	87
3	55	92
3	39	86
3	36	85
2	43	90
1	50	101
3	55	94
3	43	86
3	60	86
2	48	90
1	30	75
3	43	86
3	39	91
3	52	97
2	39	91
3	39	70
2	56	98
3	59	96
3	46	95
2	57	100
3	50	95
3	54	97
3	50	97
3	60	92
1	59	115
3	41	88
2	48	87
3	59	100
3	60	98
1	56	102
3	51	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185655&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185655&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185655&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
MOMAGE ~ WISCRY7V
means2.3332.143222.52222.333322.52331.62.251.66721.66731122.8891.8572.4292.42.22.8332.1252.2732.62.52.4

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MOMAGE  ~  WISCRY7V \tabularnewline
means & 2.333 & 2.143 & 2 & 2 & 2.5 & 2 & 2 & 2 & 2.333 & 3 & 2 & 2.5 & 2 & 3 & 3 & 1.6 & 2.25 & 1.667 & 2 & 1.667 & 3 & 1 & 1 & 2 & 2.889 & 1.857 & 2.429 & 2.4 & 2.2 & 2.833 & 2.125 & 2.273 & 2.6 & 2.5 & 2.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185655&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]MOMAGE  ~  WISCRY7V[/C][/ROW]
[ROW][C]means[/C][C]2.333[/C][C]2.143[/C][C]2[/C][C]2[/C][C]2.5[/C][C]2[/C][C]2[/C][C]2[/C][C]2.333[/C][C]3[/C][C]2[/C][C]2.5[/C][C]2[/C][C]3[/C][C]3[/C][C]1.6[/C][C]2.25[/C][C]1.667[/C][C]2[/C][C]1.667[/C][C]3[/C][C]1[/C][C]1[/C][C]2[/C][C]2.889[/C][C]1.857[/C][C]2.429[/C][C]2.4[/C][C]2.2[/C][C]2.833[/C][C]2.125[/C][C]2.273[/C][C]2.6[/C][C]2.5[/C][C]2.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185655&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185655&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 ~ WISCRY7V
means2.3332.143222.52222.333322.52331.62.251.66721.66731122.8891.8572.4292.42.22.8332.1252.2732.62.52.4







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
WISCRY7V35792.07622.63134.1270
Residuals11676.9240.663

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
WISCRY7V & 35 & 792.076 & 22.631 & 34.127 & 0 \tabularnewline
Residuals & 116 & 76.924 & 0.663 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185655&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]WISCRY7V[/C][C]35[/C][C]792.076[/C][C]22.631[/C][C]34.127[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]116[/C][C]76.924[/C][C]0.663[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185655&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185655&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)
WISCRY7V35792.07622.63134.1270
Residuals11676.9240.663







Must Include Intercept to use Tukey Test

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185655&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185655&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185655&T=3

As an alternative you can also use a QR Code:  

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

Must Include Intercept to use Tukey Test







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group340.9060.619
116

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 34 & 0.906 & 0.619 \tabularnewline
  & 116 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185655&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]34[/C][C]0.906[/C][C]0.619[/C][/ROW]
[ROW][C] [/C][C]116[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185655&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185655&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)
Group340.9060.619
116



Parameters (Session):
par1 = 1 ; par2 = 3 ; par3 = FALSE ;
Parameters (R input):
par1 = 1 ; par2 = 3 ; par3 = FALSE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '3'
par1 <- '1'
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')