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Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Sat, 27 Oct 2012 17:39:54 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/27/t1351374034d624ynv5792vc1h.htm/, Retrieved Thu, 02 May 2024 14:47:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=184279, Retrieved Thu, 02 May 2024 14:47:32 +0000

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-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Q6] [2012-10-27 21:39:54] [0ce3a3cc7b36ec2616d0d876d7c7ef2d] [Current]

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Histogram

Boxplots

1	1	4	0	2	'T'	0	3	-1	1	4
1	1	0	0	2	'T'	0	-1	-1	1	0
0	1	4	1	1.5	'T'	1	4	1	1.5	5
0	0	0	0	0	'T'	0	0	0	0	0
1	1	0	1	1	'T'	0	-1	0	0	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	0	1	2	'T'	0	-1	0	1	0
0	1	0	1	1	'T'	1	0	1	1	1
0	1	4	1	2	'T'	1	4	1	2	5
1	1	1	0	2	'T'	0	0	-1	1	1
0	0	4	0	2	'T'	0	4	0	2	4
0	1	0	1	0	'T'	1	0	1	0	1
0	1	2	1	0	'T'	1	2	1	0	3
0	1	0	0	2	'T'	1	0	0	2	1
0	0	0	NA	NA	'T'	0	0	NA	NA	0
1	1	0	1	2	'T'	0	-1	0	1	0
1	1	1	0	2	'T'	0	0	-1	1	1
1	1	0	1	0.5	'T'	0	-1	0	-0.5	0
0	1	0	1	2	'T'	1	0	1	2	1
0	0	2	1	0	'T'	0	2	1	0	2
1	1	2	1	2	'T'	0	1	0	1	2
1	1	1	0	0	'T'	0	0	-1	-1	1
0	0	2	NA	NA	'T'	0	2	NA	NA	2
1	0	0	NA	NA	'T'	-1	-1	NA	NA	-1
1	1	3	1	2	'T'	0	2	0	1	3
1	0	0	1	0	'T'	-1	-1	0	-1	-1
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
0	0	0	NA	NA	'T'	0	0	NA	NA	0
0	0	1	0	2	'T'	0	1	0	2	1
1	1	0	1	1	'T'	0	-1	0	0	0
1	0	0	0	0.5	'T'	-1	-1	-1	-0.5	-1
1	1	4	0	2	'T'	0	3	-1	1	4
0	0	0	1	0.5	'T'	0	0	1	0.5	0
0	0	1	NA	NA	'T'	0	1	NA	NA	1
0	0	0	1	0.5	'T'	0	0	1	0.5	0
1	1	0	NA	NA	'T'	0	-1	NA	NA	0
1	1	4	0	2	'T'	0	3	-1	1	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=184279&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=184279&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184279&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

ANOVA Model
post1-pre ~ post4
means	0.167	-0.417	0.167	0.833	0.021	-0.31

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post1-pre  ~  post4 \tabularnewline
means & 0.167 & -0.417 & 0.167 & 0.833 & 0.021 & -0.31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184279&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post1-pre  ~  post4[/C][/ROW]
[ROW][C]means[/C][C]0.167[/C][C]-0.417[/C][C]0.167[/C][C]0.833[/C][C]0.021[/C][C]-0.31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184279&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184279&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
post1-pre ~ post4
means	0.167	-0.417	0.167	0.833	0.021	-0.31

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
post4	5	2.023	0.405	1.662	0.173
Residuals	31	7.545	0.243

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post4 & 5 & 2.023 & 0.405 & 1.662 & 0.173 \tabularnewline
Residuals & 31 & 7.545 & 0.243 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184279&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]post4[/C][C]5[/C][C]2.023[/C][C]0.405[/C][C]1.662[/C][C]0.173[/C][/ROW]
[ROW][C]Residuals[/C][C]31[/C][C]7.545[/C][C]0.243[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184279&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184279&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
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
post4	5	2.023	0.405	1.662	0.173
Residuals	31	7.545	0.243

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
0.5-0	-0.417	-1.383	0.55	0.778
1-0	0.167	-0.892	1.225	0.997
1.5-0	0.833	-0.784	2.451	0.627
2-0	0.021	-0.696	0.738	1
NA-0	-0.31	-1.143	0.524	0.866
1-0.5	0.583	-0.56	1.727	0.637
1.5-0.5	1.25	-0.424	2.924	0.238
2-0.5	0.437	-0.4	1.275	0.613
NA-0.5	0.107	-0.831	1.046	0.999
1.5-1	0.667	-1.062	2.396	0.847
2-1	-0.146	-1.088	0.796	0.997
NA-1	-0.476	-1.509	0.557	0.727
2-1.5	-0.812	-2.356	0.731	0.606
NA-1.5	-1.143	-2.744	0.458	0.281
NA-2	-0.33	-1.009	0.348	0.68

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0.5-0 & -0.417 & -1.383 & 0.55 & 0.778 \tabularnewline
1-0 & 0.167 & -0.892 & 1.225 & 0.997 \tabularnewline
1.5-0 & 0.833 & -0.784 & 2.451 & 0.627 \tabularnewline
2-0 & 0.021 & -0.696 & 0.738 & 1 \tabularnewline
NA-0 & -0.31 & -1.143 & 0.524 & 0.866 \tabularnewline
1-0.5 & 0.583 & -0.56 & 1.727 & 0.637 \tabularnewline
1.5-0.5 & 1.25 & -0.424 & 2.924 & 0.238 \tabularnewline
2-0.5 & 0.437 & -0.4 & 1.275 & 0.613 \tabularnewline
NA-0.5 & 0.107 & -0.831 & 1.046 & 0.999 \tabularnewline
1.5-1 & 0.667 & -1.062 & 2.396 & 0.847 \tabularnewline
2-1 & -0.146 & -1.088 & 0.796 & 0.997 \tabularnewline
NA-1 & -0.476 & -1.509 & 0.557 & 0.727 \tabularnewline
2-1.5 & -0.812 & -2.356 & 0.731 & 0.606 \tabularnewline
NA-1.5 & -1.143 & -2.744 & 0.458 & 0.281 \tabularnewline
NA-2 & -0.33 & -1.009 & 0.348 & 0.68 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184279&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]0.5-0[/C][C]-0.417[/C][C]-1.383[/C][C]0.55[/C][C]0.778[/C][/ROW]
[ROW][C]1-0[/C][C]0.167[/C][C]-0.892[/C][C]1.225[/C][C]0.997[/C][/ROW]
[ROW][C]1.5-0[/C][C]0.833[/C][C]-0.784[/C][C]2.451[/C][C]0.627[/C][/ROW]
[ROW][C]2-0[/C][C]0.021[/C][C]-0.696[/C][C]0.738[/C][C]1[/C][/ROW]
[ROW][C]NA-0[/C][C]-0.31[/C][C]-1.143[/C][C]0.524[/C][C]0.866[/C][/ROW]
[ROW][C]1-0.5[/C][C]0.583[/C][C]-0.56[/C][C]1.727[/C][C]0.637[/C][/ROW]
[ROW][C]1.5-0.5[/C][C]1.25[/C][C]-0.424[/C][C]2.924[/C][C]0.238[/C][/ROW]
[ROW][C]2-0.5[/C][C]0.437[/C][C]-0.4[/C][C]1.275[/C][C]0.613[/C][/ROW]
[ROW][C]NA-0.5[/C][C]0.107[/C][C]-0.831[/C][C]1.046[/C][C]0.999[/C][/ROW]
[ROW][C]1.5-1[/C][C]0.667[/C][C]-1.062[/C][C]2.396[/C][C]0.847[/C][/ROW]
[ROW][C]2-1[/C][C]-0.146[/C][C]-1.088[/C][C]0.796[/C][C]0.997[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.476[/C][C]-1.509[/C][C]0.557[/C][C]0.727[/C][/ROW]
[ROW][C]2-1.5[/C][C]-0.812[/C][C]-2.356[/C][C]0.731[/C][C]0.606[/C][/ROW]
[ROW][C]NA-1.5[/C][C]-1.143[/C][C]-2.744[/C][C]0.458[/C][C]0.281[/C][/ROW]
[ROW][C]NA-2[/C][C]-0.33[/C][C]-1.009[/C][C]0.348[/C][C]0.68[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184279&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184279&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
	diff	lwr	upr	p adj
0.5-0	-0.417	-1.383	0.55	0.778
1-0	0.167	-0.892	1.225	0.997
1.5-0	0.833	-0.784	2.451	0.627
2-0	0.021	-0.696	0.738	1
NA-0	-0.31	-1.143	0.524	0.866
1-0.5	0.583	-0.56	1.727	0.637
1.5-0.5	1.25	-0.424	2.924	0.238
2-0.5	0.437	-0.4	1.275	0.613
NA-0.5	0.107	-0.831	1.046	0.999
1.5-1	0.667	-1.062	2.396	0.847
2-1	-0.146	-1.088	0.796	0.997
NA-1	-0.476	-1.509	0.557	0.727
2-1.5	-0.812	-2.356	0.731	0.606
NA-1.5	-1.143	-2.744	0.458	0.281
NA-2	-0.33	-1.009	0.348	0.68

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	0.598	0.701
	31

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 0.598 & 0.701 \tabularnewline
  & 31 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184279&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]5[/C][C]0.598[/C][C]0.701[/C][/ROW]
[ROW][C] [/C][C]31[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184279&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184279&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
	Df	F value	Pr(>F)
Group	5	0.598	0.701
	31

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 9 ; par2 = 7 ; par3 = TRUE ;

Parameters (R input):

par1 = 7 ; par2 = 5 ; par3 = TRUE ;

R code (references can be found in the software module):

par3 <- 'TRUE'
par2 <- '5'
par1 <- '7  9'
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code