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Author's title

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

Tue, 02 Nov 2010 13:45:56 +0000

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/2010/Nov/02/t12887054969n7645nbqnvl3q7.htm/, Retrieved Sun, 28 Apr 2024 10:39:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91461, Retrieved Sun, 28 Apr 2024 10:39:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

141

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)] [Simulation experi...] [2010-10-26 10:02:07] [b98453cac15ba1066b407e146608df68]
-   PD  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws 5 - question 6] [2010-10-29 14:20:23] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
-    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Vraag6] [2010-11-02 13:45:56] [9be3691a9b6ce074cb51fd18377fce28] [Current]

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Dataseries X:

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Histogram

Boxplots

1	1	0	'T'
1	1	0	'T'
0	1	1	'T'
0	0	0	'T'
1	1	1	'T'
1	1	1	'T'
1	1	1	'T'
0	1	1	'T'
0	1	1	'T'
1	1	0	'T'
0	0	0	'T'
0	1	1	'T'
0	1	1	'T'
0	1	0	'T'
0	0		'T'
1	1	1	'T'
1	1	0	'T'
1	1	1	'T'
0	1	1	'T'
0	0	1	'T'
1	1	1	'T'
1	1	0	'T'
0	0		'T'
1	0		'T'
1	1	1	'T'
1	0	1	'T'
1	1		'T'
0	0		'T'
0	0	0	'T'
1	1	1	'T'
1	0	0	'T'
1	1	0	'T'
0	0	1	'T'
0	0		'T'
0	0	1	'T'
1	1		'T'
1	1	0	'T'
0	1	1	'E'
0	1	1	'E'
1	1	1	'E'
1	1	1	'E'
1	1	1	'E'
1	1	0	'E'
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0	0	1	'E'
0	1	1	'E'
0	1	0	'E'
1	1	0	'E'
1	1	1	'E'
0	0	0	'E'
0	1	1	'E'
1	1	1	'E'
0	1	1	'E'
0	0		'E'
0	1	0	'E'
0	1	1	'E'
0	1	1	'E'
0	1		'E'
0	0	0	'E'
0	0		'E'
0	1	1	'E'
1	1	1	'E'
1	1	1	'E'
1	0	1	'E'
0	0	1	'E'
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0	0	0	'E'
1	1	1	'E'
1	1	1	'E'
0	1	0	'S'
0	1	0	'S'
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0	1	0	'S'
1	1	1	'S'
1	0	1	'S'
0	0	1	'S'
1	1	1	'S'
1	0	1	'S'
1	1	1	'S'
0	0	1	'S'
0	0	1	'S'
0	0	1	'S'
1	0	1	'S'
0	0		'S'
0	0	1	'S'
1	0		'S'
1	1	1	'S'
0	0	1	'S'
0	0		'S'
1	1	0	'S'
1	1	1	'S'
1	1		'S'
0	1	1	'S'
1	1	1	'S'
1	1	1	'S'
1	1	1	'S'
1	1	1	'S'
0	0		'S'
0	0	0	'S'
1	1	0	'S'
0	0	1	'S'
0	0	0	'S'
0	0	1	'S'
0	1	0	'S'

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91461&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91461&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91461&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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

ANOVA Model
post-test1 ~ treatment
means	0.5	-0.052	0.25	0.167	0.367

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post-test1  ~  treatment \tabularnewline
means & 0.5 & -0.052 & 0.25 & 0.167 & 0.367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91461&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post-test1  ~  treatment[/C][/ROW]
[ROW][C]means[/C][C]0.5[/C][C]-0.052[/C][C]0.25[/C][C]0.167[/C][C]0.367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91461&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91461&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
post-test1 ~ treatment
means	0.5	-0.052	0.25	0.167	0.367

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
treatment	4	2.002	0.5	2.155	0.084
Residuals	66	15.322	0.232

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
treatment & 4 & 2.002 & 0.5 & 2.155 & 0.084 \tabularnewline
Residuals & 66 & 15.322 & 0.232 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91461&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]treatment[/C][C]4[/C][C]2.002[/C][C]0.5[/C][C]2.155[/C][C]0.084[/C][/ROW]
[ROW][C]Residuals[/C][C]66[/C][C]15.322[/C][C]0.232[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91461&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91461&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)
treatment	4	2.002	0.5	2.155	0.084
Residuals	66	15.322	0.232

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
1-0	-0.052	-0.445	0.341	0.996
E-0	0.25	-0.49	0.99	0.877
S-0	0.167	-0.67	1.003	0.98
T-0	0.367	-0.095	0.828	0.182
E-1	0.302	-0.419	1.022	0.766
S-1	0.218	-0.601	1.038	0.944
T-1	0.418	-0.011	0.848	0.06
S-E	-0.083	-1.115	0.949	0.999
T-E	0.117	-0.644	0.877	0.993
T-S	0.2	-0.655	1.055	0.965

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -0.052 & -0.445 & 0.341 & 0.996 \tabularnewline
E-0 & 0.25 & -0.49 & 0.99 & 0.877 \tabularnewline
S-0 & 0.167 & -0.67 & 1.003 & 0.98 \tabularnewline
T-0 & 0.367 & -0.095 & 0.828 & 0.182 \tabularnewline
E-1 & 0.302 & -0.419 & 1.022 & 0.766 \tabularnewline
S-1 & 0.218 & -0.601 & 1.038 & 0.944 \tabularnewline
T-1 & 0.418 & -0.011 & 0.848 & 0.06 \tabularnewline
S-E & -0.083 & -1.115 & 0.949 & 0.999 \tabularnewline
T-E & 0.117 & -0.644 & 0.877 & 0.993 \tabularnewline
T-S & 0.2 & -0.655 & 1.055 & 0.965 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91461&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]-0.052[/C][C]-0.445[/C][C]0.341[/C][C]0.996[/C][/ROW]
[ROW][C]E-0[/C][C]0.25[/C][C]-0.49[/C][C]0.99[/C][C]0.877[/C][/ROW]
[ROW][C]S-0[/C][C]0.167[/C][C]-0.67[/C][C]1.003[/C][C]0.98[/C][/ROW]
[ROW][C]T-0[/C][C]0.367[/C][C]-0.095[/C][C]0.828[/C][C]0.182[/C][/ROW]
[ROW][C]E-1[/C][C]0.302[/C][C]-0.419[/C][C]1.022[/C][C]0.766[/C][/ROW]
[ROW][C]S-1[/C][C]0.218[/C][C]-0.601[/C][C]1.038[/C][C]0.944[/C][/ROW]
[ROW][C]T-1[/C][C]0.418[/C][C]-0.011[/C][C]0.848[/C][C]0.06[/C][/ROW]
[ROW][C]S-E[/C][C]-0.083[/C][C]-1.115[/C][C]0.949[/C][C]0.999[/C][/ROW]
[ROW][C]T-E[/C][C]0.117[/C][C]-0.644[/C][C]0.877[/C][C]0.993[/C][/ROW]
[ROW][C]T-S[/C][C]0.2[/C][C]-0.655[/C][C]1.055[/C][C]0.965[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91461&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91461&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
1-0	-0.052	-0.445	0.341	0.996
E-0	0.25	-0.49	0.99	0.877
S-0	0.167	-0.67	1.003	0.98
T-0	0.367	-0.095	0.828	0.182
E-1	0.302	-0.419	1.022	0.766
S-1	0.218	-0.601	1.038	0.944
T-1	0.418	-0.011	0.848	0.06
S-E	-0.083	-1.115	0.949	0.999
T-E	0.117	-0.644	0.877	0.993
T-S	0.2	-0.655	1.055	0.965

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	4	2.254	0.073
	66

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 2.254 & 0.073 \tabularnewline
  & 66 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91461&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]4[/C][C]2.254[/C][C]0.073[/C][/ROW]
[ROW][C] [/C][C]66[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91461&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91461&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	4	2.254	0.073
	66

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = 4 ; par3 = TRUE ;

Parameters (R input):

par1 = 2 ; par2 = 4 ; 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