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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 computationWed, 17 Dec 2014 18:56:44 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t14188453809f159jr6kxu3y6h.htm/, Retrieved Thu, 31 Oct 2024 23:24:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270613, Retrieved Thu, 31 Oct 2024 23:24:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
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Estimated Impact96
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)] [] [2014-12-17 18:56:44] [6341ece6c012999a305a5ce37b6a24ca] [Current]
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Dataseries X:
0	50
1	62
0	54
1	71
1	54
1	65
0	73
1	52
1	84
1	42
1	66
1	65
1	78
0	73
0	75
0	72
1	66
0	70
1	61
0	81
1	71
1	69
0	71
1	72
1	68
1	70
1	68
0	61
1	67
0	76
0	70
0	60
1	72
1	69
1	71
1	62
0	70
1	64
1	58
0	76
1	52
1	59
1	68
1	76
1	65
0	67
1	59
1	69
0	76
1	63
1	75
1	63
1	60
1	73
1	63
1	70
0	75
1	66
0	63
1	63
1	64
0	70
0	75
1	61
0	60
1	62
0	73
1	61
1	66
0	64
0	59
0	64
0	60
1	56
0	78
0	67
1	59
0	66
0	68
1	71
0	66
0	73
0	72
1	71
0	59
1	64
1	66
0	78
0	68
0	73
1	62
1	65
1	68
0	65
1	60
0	71
1	65
1	68
1	64
1	74
1	69
0	76
1	68
1	72
1	67
0	63
0	59
0	73
0	66
0	62
0	69
1	66
1	51
1	56
1	67
1	69
0	57
1	56
1	55
0	63
1	67
0	65
0	47
1	76
1	64
1	68
1	64
1	65
1	71
1	63
1	60
0	68
1	72
1	70
1	61
1	61
1	62
1	71
0	71
1	51
1	56
1	70
1	73
1	76
0	68
0	48
1	52
0	60
0	59
1	57
0	79
1	60
1	60
0	59
1	62
1	59
1	61
0	71
0	57
0	66
0	63
1	69
0	58
1	59
0	48
1	66
0	73
1	67
0	61
0	68
1	75
0	62
1	69
1	58
1	60
1	74
1	55
0	62
1	63
0	69
0	58
0	58
1	68
0	72
1	62
0	62
0	65
0	69
0	66
1	72
1	62
1	75
1	58
0	66
0	55
1	47
0	72
0	62
0	64
0	64
1	19
1	50
0	68
0	70
1	79
0	69
1	71
1	48
0	73
1	74
1	66
1	71
0	74
0	78
0	75
1	53
1	60
1	70
1	69
0	65
0	78
0	78
1	59
1	72
0	70
0	63
0	63
1	71
1	74
0	67
0	66
0	62
1	80
1	73
1	67
1	61
0	73
1	74
1	32
1	69
0	69
0	84
1	64
0	58
1	59
1	78
0	57
1	60
0	68
1	68
1	73
0	69
1	67
0	60
1	65
0	66
1	74
0	81
0	72
1	55
1	49
0	74
1	53
1	64
0	65
1	57
0	51
0	80
1	67
1	70
0	74
1	75
0	70
0	69
1	65
0	55
0	71
1	65




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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270613&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270613&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270613&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







ANOVA Model
AMS.E ~ gender
means66.917-2.391

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
AMS.E  ~  gender \tabularnewline
means & 66.917 & -2.391 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270613&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]AMS.E  ~  gender[/C][/ROW]
[ROW][C]means[/C][C]66.917[/C][C]-2.391[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270613&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270613&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
AMS.E ~ gender
means66.917-2.391







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
gender1390.014390.0145.9770.015
Residuals27618008.56565.248

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
gender & 1 & 390.014 & 390.014 & 5.977 & 0.015 \tabularnewline
Residuals & 276 & 18008.565 & 65.248 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270613&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]gender[/C][C]1[/C][C]390.014[/C][C]390.014[/C][C]5.977[/C][C]0.015[/C][/ROW]
[ROW][C]Residuals[/C][C]276[/C][C]18008.565[/C][C]65.248[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270613&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270613&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)
gender1390.014390.0145.9770.015
Residuals27618008.56565.248







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-2.391-4.317-0.4660.015

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -2.391 & -4.317 & -0.466 & 0.015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270613&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]1-0[/C][C]-2.391[/C][C]-4.317[/C][C]-0.466[/C][C]0.015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270613&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270613&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
1-0-2.391-4.317-0.4660.015







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.1090.741
276

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.109 & 0.741 \tabularnewline
  & 276 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270613&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]1[/C][C]0.109[/C][C]0.741[/C][/ROW]
[ROW][C] [/C][C]276[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270613&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270613&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)
Group10.1090.741
276



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):
par3 <- 'TRUE'
par2 <- '2'
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')