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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

Mon, 17 Dec 2012 12:43:06 -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/2012/Dec/17/t1355766348d0t60hqnlhilo1y.htm/, Retrieved Tue, 16 Apr 2024 19:23:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201091, Retrieved Tue, 16 Apr 2024 19:23:47 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

127

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)] [Paper 3 - One way...] [2012-12-10 15:07:54] [d7df2128d8ee42e4ceceb756b40e5412]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [paper deel 3 Anova] [2012-12-17 17:43:06] [2382f403a285d81cd69bebfa1420b1d7] [Current]

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Dataseries X:

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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
0	1	1	1	0	'E'	1	1	1	0	2
0	1	0	1	1	'E'	1	0	1	1	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	0	0	'E'	0	-1	-1	-1	0
1	1	0	1	0,5	'E'	0	-1	0	-0,5	0
0	0	0	1	0	'E'	0	0	1	0	0
0	1	4	1	2	'E'	1	4	1	2	5
0	1	0	0	0	'E'	1	0	0	0	1
1	1	0	0	1	'E'	0	-1	-1	0	0
1	1	4	1	2	'E'	0	3	0	1	4
0	0	4	0	0,5	'E'	0	4	0	0,5	4
0	1	0	1	2	'E'	1	0	1	2	1
1	1	1	1	2	'E'	0	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	4	NA	NA	'E'	0	4	NA	NA	4
0	1	0	0	0	'E'	1	0	0	0	1
0	1	2	1	0	'E'	1	2	1	0	3
0	1	0	1	0,5	'E'	1	0	1	0,5	1
0	1	4	NA	NA	'E'	1	4	NA	NA	5
0	0	4	0	2	'E'	0	4	0	2	4
0	0	0	NA	NA	'E'	0	0	NA	NA	0
0	1	0	1	0	'E'	1	0	1	0	1
1	1	4	1	2	'E'	0	3	0	1	4
1	1	0	1	1	'E'	0	-1	0	0	0
1	0	0	1	0	'E'	-1	-1	0	-1	-1
0	0	2	1	2	'E'	0	2	1	2	2
0	1	0	0	1	'E'	1	0	0	1	1
0	1	0	1	2	'E'	1	0	1	2	1
0	0	0	0	0	'E'	0	0	0	0	0
1	1	4	1	1	'E'	0	3	0	0	4
1	1	4	1	2	'E'	0	3	0	1	4
0	1	2	0	0	'S'	1	2	0	0	3
0	1	0	0	0	'S'	1	0	0	0	1
0	1	0	0	0	'S'	1	0	0	0	1
0	1	4	0	0	'S'	1	4	0	0	5
1	1	0	1	2	'S'	0	-1	0	1	0
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	1	1	2	'S'	0	1	1	2	1
1	1	2	1	2	'S'	0	1	0	1	2
1	0	0	1	2	'S'	-1	-1	0	1	-1
1	1	2	1	2	'S'	0	1	0	1	2
0	0	0	1	2	'S'	0	0	1	2	0
0	0	4	1	2	'S'	0	4	1	2	4
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	1	2	'S'	-1	-1	0	1	-1
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	4	1	2	'S'	0	4	1	2	4
1	0	0	NA	NA	'S'	-1	-1	NA	NA	-1
1	1	4	1	2	'S'	0	3	0	1	4
0	0	2	1	2	'S'	0	2	1	2	2
0	0	2	NA	NA	'S'	0	2	NA	NA	2
1	1	0	0	0	'S'	0	-1	-1	-1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	NA	NA	'S'	0	3	NA	NA	4
0	1	0	1	2	'S'	1	0	1	2	1
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	0	1	2	'S'	0	-1	0	1	0
1	1	4	1	2	'S'	0	3	0	1	4
1	1	4	1	2	'S'	0	3	0	1	4
0	0	0	NA	NA	'S'	0	0	NA	NA	0
0	0	0	0	0	'S'	0	0	0	0	0
1	1	2	0	0	'S'	0	1	-1	-1	2
0	0	1	1	2	'S'	0	1	1	2	1
0	0	0	0	0	'S'	0	0	0	0	0
0	0	2	1	2	'S'	0	2	1	2	2
0	1	1	0	0	'S'	1	1	0	0	2

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
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

\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
R Framework error message & The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201091&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]
[ROW][C]R Framework error message[/C][C]The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201091&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201091&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
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

ANOVA Model
post1-pre ~ post2-pre
means	-0.296	0.781	0.496	0.596	0.296	0.713

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post1-pre  ~  post2-pre \tabularnewline
means & -0.296 & 0.781 & 0.496 & 0.596 & 0.296 & 0.713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201091&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post1-pre  ~  post2-pre[/C][/ROW]
[ROW][C]means[/C][C]-0.296[/C][C]0.781[/C][C]0.496[/C][C]0.596[/C][C]0.296[/C][C]0.713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201091&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201091&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 ~ post2-pre
means	-0.296	0.781	0.496	0.596	0.296	0.713

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
post2-pre	5	10.426	2.085	10.075	0
Residuals	99	20.489	0.207

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post2-pre & 5 & 10.426 & 2.085 & 10.075 & 0 \tabularnewline
Residuals & 99 & 20.489 & 0.207 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201091&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]post2-pre[/C][C]5[/C][C]10.426[/C][C]2.085[/C][C]10.075[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]99[/C][C]20.489[/C][C]0.207[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201091&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201091&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)
post2-pre	5	10.426	2.085	10.075	0
Residuals	99	20.489	0.207

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
0--1	0.781	0.438	1.124	0
1--1	0.496	0.007	0.986	0.045
2--1	0.596	0.107	1.086	0.008
3--1	0.296	-0.15	0.743	0.391
4--1	0.713	0.254	1.172	0
1-0	-0.285	-0.762	0.192	0.513
2-0	-0.185	-0.662	0.292	0.87
3-0	-0.485	-0.918	-0.052	0.019
4-0	-0.068	-0.514	0.378	0.998
2-1	0.1	-0.491	0.691	0.996
3-1	-0.2	-0.756	0.356	0.901
4-1	0.217	-0.349	0.783	0.875
3-2	-0.3	-0.856	0.256	0.621
4-2	0.117	-0.449	0.683	0.991
4-3	0.417	-0.113	0.946	0.209

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & 0.781 & 0.438 & 1.124 & 0 \tabularnewline
1--1 & 0.496 & 0.007 & 0.986 & 0.045 \tabularnewline
2--1 & 0.596 & 0.107 & 1.086 & 0.008 \tabularnewline
3--1 & 0.296 & -0.15 & 0.743 & 0.391 \tabularnewline
4--1 & 0.713 & 0.254 & 1.172 & 0 \tabularnewline
1-0 & -0.285 & -0.762 & 0.192 & 0.513 \tabularnewline
2-0 & -0.185 & -0.662 & 0.292 & 0.87 \tabularnewline
3-0 & -0.485 & -0.918 & -0.052 & 0.019 \tabularnewline
4-0 & -0.068 & -0.514 & 0.378 & 0.998 \tabularnewline
2-1 & 0.1 & -0.491 & 0.691 & 0.996 \tabularnewline
3-1 & -0.2 & -0.756 & 0.356 & 0.901 \tabularnewline
4-1 & 0.217 & -0.349 & 0.783 & 0.875 \tabularnewline
3-2 & -0.3 & -0.856 & 0.256 & 0.621 \tabularnewline
4-2 & 0.117 & -0.449 & 0.683 & 0.991 \tabularnewline
4-3 & 0.417 & -0.113 & 0.946 & 0.209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201091&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--1[/C][C]0.781[/C][C]0.438[/C][C]1.124[/C][C]0[/C][/ROW]
[ROW][C]1--1[/C][C]0.496[/C][C]0.007[/C][C]0.986[/C][C]0.045[/C][/ROW]
[ROW][C]2--1[/C][C]0.596[/C][C]0.107[/C][C]1.086[/C][C]0.008[/C][/ROW]
[ROW][C]3--1[/C][C]0.296[/C][C]-0.15[/C][C]0.743[/C][C]0.391[/C][/ROW]
[ROW][C]4--1[/C][C]0.713[/C][C]0.254[/C][C]1.172[/C][C]0[/C][/ROW]
[ROW][C]1-0[/C][C]-0.285[/C][C]-0.762[/C][C]0.192[/C][C]0.513[/C][/ROW]
[ROW][C]2-0[/C][C]-0.185[/C][C]-0.662[/C][C]0.292[/C][C]0.87[/C][/ROW]
[ROW][C]3-0[/C][C]-0.485[/C][C]-0.918[/C][C]-0.052[/C][C]0.019[/C][/ROW]
[ROW][C]4-0[/C][C]-0.068[/C][C]-0.514[/C][C]0.378[/C][C]0.998[/C][/ROW]
[ROW][C]2-1[/C][C]0.1[/C][C]-0.491[/C][C]0.691[/C][C]0.996[/C][/ROW]
[ROW][C]3-1[/C][C]-0.2[/C][C]-0.756[/C][C]0.356[/C][C]0.901[/C][/ROW]
[ROW][C]4-1[/C][C]0.217[/C][C]-0.349[/C][C]0.783[/C][C]0.875[/C][/ROW]
[ROW][C]3-2[/C][C]-0.3[/C][C]-0.856[/C][C]0.256[/C][C]0.621[/C][/ROW]
[ROW][C]4-2[/C][C]0.117[/C][C]-0.449[/C][C]0.683[/C][C]0.991[/C][/ROW]
[ROW][C]4-3[/C][C]0.417[/C][C]-0.113[/C][C]0.946[/C][C]0.209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201091&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201091&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--1	0.781	0.438	1.124	0
1--1	0.496	0.007	0.986	0.045
2--1	0.596	0.107	1.086	0.008
3--1	0.296	-0.15	0.743	0.391
4--1	0.713	0.254	1.172	0
1-0	-0.285	-0.762	0.192	0.513
2-0	-0.185	-0.662	0.292	0.87
3-0	-0.485	-0.918	-0.052	0.019
4-0	-0.068	-0.514	0.378	0.998
2-1	0.1	-0.491	0.691	0.996
3-1	-0.2	-0.756	0.356	0.901
4-1	0.217	-0.349	0.783	0.875
3-2	-0.3	-0.856	0.256	0.621
4-2	0.117	-0.449	0.683	0.991
4-3	0.417	-0.113	0.946	0.209

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	2.418	0.041
	99

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 2.418 & 0.041 \tabularnewline
  & 99 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201091&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]2.418[/C][C]0.041[/C][/ROW]
[ROW][C] [/C][C]99[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201091&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201091&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	2.418	0.041
	99

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 7 ; par2 = 6 ; par3 = TRUE ;

Parameters (R input):

par1 = 7 ; par2 = 6 ; par3 = TRUE ;

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

par3 <- 'TRUE'
par2 <- '8'
par1 <- '7'
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