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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

Sun, 18 Dec 2011 13:22:05 -0500

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/2011/Dec/18/t1324232539x9t1352obfh40cz.htm/, Retrieved Thu, 02 May 2024 22:27:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157113, Retrieved Thu, 02 May 2024 22:27:44 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

104

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)] [] [2010-11-01 13:37:53] [b98453cac15ba1066b407e146608df68]
-   PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [D1 1A] [2011-12-18 18:22:05] [cdf03f2f7d2bbe3f2da091606ae8e03f] [Current]
- R PD      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Paper (13)] [2012-12-21 09:23:10] [300ac07a477d84a470eebba12c2af4b2] 

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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	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157113&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157113&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157113&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	'Herman Ole Andreas Wold' @ wold.wessa.net

ANOVA Model
Interestvoet ~ Stad
means	13.194	-0.583	0.112	0.05	0.289	-0.994

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Interestvoet  ~  Stad \tabularnewline
means & 13.194 & -0.583 & 0.112 & 0.05 & 0.289 & -0.994 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157113&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Interestvoet  ~  Stad[/C][/ROW]
[ROW][C]means[/C][C]13.194[/C][C]-0.583[/C][C]0.112[/C][C]0.05[/C][C]0.289[/C][C]-0.994[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157113&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157113&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
Interestvoet ~ Stad
means	13.194	-0.583	0.112	0.05	0.289	-0.994

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Stad	5	10.946	2.189	4.829	0.001
Residuals	48	21.758	0.453

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Stad & 5 & 10.946 & 2.189 & 4.829 & 0.001 \tabularnewline
Residuals & 48 & 21.758 & 0.453 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157113&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]Stad[/C][C]5[/C][C]10.946[/C][C]2.189[/C][C]4.829[/C][C]0.001[/C][/ROW]
[ROW][C]Residuals[/C][C]48[/C][C]21.758[/C][C]0.453[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157113&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157113&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)
Stad	5	10.946	2.189	4.829	0.001
Residuals	48	21.758	0.453

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
2-1	-0.583	-1.525	0.359	0.452
3-1	0.112	-0.83	1.054	0.999
4-1	0.05	-0.892	0.992	1
5-1	0.289	-0.653	1.231	0.942
6-1	-0.994	-1.936	-0.052	0.033
3-2	0.696	-0.246	1.638	0.261
4-2	0.633	-0.309	1.575	0.36
5-2	0.872	-0.07	1.814	0.084
6-2	-0.411	-1.353	0.531	0.786
4-3	-0.062	-1.004	0.88	1
5-3	0.177	-0.765	1.119	0.993
6-3	-1.107	-2.049	-0.165	0.013
5-4	0.239	-0.703	1.181	0.974
6-4	-1.044	-1.986	-0.102	0.022
6-5	-1.283	-2.225	-0.341	0.002

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.583 & -1.525 & 0.359 & 0.452 \tabularnewline
3-1 & 0.112 & -0.83 & 1.054 & 0.999 \tabularnewline
4-1 & 0.05 & -0.892 & 0.992 & 1 \tabularnewline
5-1 & 0.289 & -0.653 & 1.231 & 0.942 \tabularnewline
6-1 & -0.994 & -1.936 & -0.052 & 0.033 \tabularnewline
3-2 & 0.696 & -0.246 & 1.638 & 0.261 \tabularnewline
4-2 & 0.633 & -0.309 & 1.575 & 0.36 \tabularnewline
5-2 & 0.872 & -0.07 & 1.814 & 0.084 \tabularnewline
6-2 & -0.411 & -1.353 & 0.531 & 0.786 \tabularnewline
4-3 & -0.062 & -1.004 & 0.88 & 1 \tabularnewline
5-3 & 0.177 & -0.765 & 1.119 & 0.993 \tabularnewline
6-3 & -1.107 & -2.049 & -0.165 & 0.013 \tabularnewline
5-4 & 0.239 & -0.703 & 1.181 & 0.974 \tabularnewline
6-4 & -1.044 & -1.986 & -0.102 & 0.022 \tabularnewline
6-5 & -1.283 & -2.225 & -0.341 & 0.002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157113&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]-0.583[/C][C]-1.525[/C][C]0.359[/C][C]0.452[/C][/ROW]
[ROW][C]3-1[/C][C]0.112[/C][C]-0.83[/C][C]1.054[/C][C]0.999[/C][/ROW]
[ROW][C]4-1[/C][C]0.05[/C][C]-0.892[/C][C]0.992[/C][C]1[/C][/ROW]
[ROW][C]5-1[/C][C]0.289[/C][C]-0.653[/C][C]1.231[/C][C]0.942[/C][/ROW]
[ROW][C]6-1[/C][C]-0.994[/C][C]-1.936[/C][C]-0.052[/C][C]0.033[/C][/ROW]
[ROW][C]3-2[/C][C]0.696[/C][C]-0.246[/C][C]1.638[/C][C]0.261[/C][/ROW]
[ROW][C]4-2[/C][C]0.633[/C][C]-0.309[/C][C]1.575[/C][C]0.36[/C][/ROW]
[ROW][C]5-2[/C][C]0.872[/C][C]-0.07[/C][C]1.814[/C][C]0.084[/C][/ROW]
[ROW][C]6-2[/C][C]-0.411[/C][C]-1.353[/C][C]0.531[/C][C]0.786[/C][/ROW]
[ROW][C]4-3[/C][C]-0.062[/C][C]-1.004[/C][C]0.88[/C][C]1[/C][/ROW]
[ROW][C]5-3[/C][C]0.177[/C][C]-0.765[/C][C]1.119[/C][C]0.993[/C][/ROW]
[ROW][C]6-3[/C][C]-1.107[/C][C]-2.049[/C][C]-0.165[/C][C]0.013[/C][/ROW]
[ROW][C]5-4[/C][C]0.239[/C][C]-0.703[/C][C]1.181[/C][C]0.974[/C][/ROW]
[ROW][C]6-4[/C][C]-1.044[/C][C]-1.986[/C][C]-0.102[/C][C]0.022[/C][/ROW]
[ROW][C]6-5[/C][C]-1.283[/C][C]-2.225[/C][C]-0.341[/C][C]0.002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157113&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157113&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
2-1	-0.583	-1.525	0.359	0.452
3-1	0.112	-0.83	1.054	0.999
4-1	0.05	-0.892	0.992	1
5-1	0.289	-0.653	1.231	0.942
6-1	-0.994	-1.936	-0.052	0.033
3-2	0.696	-0.246	1.638	0.261
4-2	0.633	-0.309	1.575	0.36
5-2	0.872	-0.07	1.814	0.084
6-2	-0.411	-1.353	0.531	0.786
4-3	-0.062	-1.004	0.88	1
5-3	0.177	-0.765	1.119	0.993
6-3	-1.107	-2.049	-0.165	0.013
5-4	0.239	-0.703	1.181	0.974
6-4	-1.044	-1.986	-0.102	0.022
6-5	-1.283	-2.225	-0.341	0.002

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	1.28	0.288
	48

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.28 & 0.288 \tabularnewline
  & 48 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157113&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]1.28[/C][C]0.288[/C][/ROW]
[ROW][C] [/C][C]48[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157113&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157113&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	1.28	0.288
	48

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 5 ; par2 = 4 ; par3 = TRUE ;

Parameters (R input):

par1 = 1 ; par2 = 2 ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code