## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software ModuleIan.Hollidayrwasp_Two Factor ANOVA -V2.wasp
Title produced by softwareVariability
Date of computationWed, 01 Sep 2010 14:47:50 +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/2010/Sep/01/t1283352433ahyvjpcktqccwx3.htm/, Retrieved Tue, 21 Mar 2023 07:11:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79509, Retrieved Tue, 21 Mar 2023 07:11:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [two-way anova wit...] [2010-05-26 17:02:24] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R PD  [Two-Way ANOVA] [ANOVA with good l...] [2010-05-28 23:09:47] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R       [Variability] [ANOVA with better...] [2010-05-29 09:47:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R         [Variability] [ANOVA with better...] [2010-05-29 09:54:40] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P           [Variability] [] [2010-09-01 14:47:50] [5b9d246d860ef53a68ce67017a6503a5] [Current]
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Dataseries X:
'GOOD'	'HIGH'	25
'GOOD'	'HIGH'	0
'GOOD'	'HIGH'	-16
'GOOD'	'HIGH'	5
'GOOD'	'HIGH'	11
'GOOD'	'HIGH'	-6
'GOOD'	'HIGH'	42
'GOOD'	'HIGH'	-2
'GOOD'	'HIGH'	-13
'GOOD'	'HIGH'	14
'GOOD'	'HIGH'	4
'GOOD'	'HIGH'	-22
'GOOD'	'HIGH'	19
'GOOD'	'HIGH'	6
'GOOD'	'HIGH'	-6
'GOOD'	'LOW'	-25
'GOOD'	'LOW'	-23
'GOOD'	'LOW'	-28
'GOOD'	'LOW'	-22
'GOOD'	'LOW'	-22
'GOOD'	'LOW'	-10
'GOOD'	'LOW'	-20
'GOOD'	'LOW'	-24
'GOOD'	'LOW'	-24
'GOOD'	'LOW'	-22
'GOOD'	'LOW'	-23
'GOOD'	'LOW'	-19
'GOOD'	'LOW'	-2
'GOOD'	'LOW'	12
'GOOD'	'LOW'	-8
'GOOD'	'LOW'	-17
'GOOD'	'LOW'	-30
'SCIENTIFIC'	'HIGH'	-19
'SCIENTIFIC'	'HIGH'	-24
'SCIENTIFIC'	'HIGH'	-4
'SCIENTIFIC'	'HIGH'	-24
'SCIENTIFIC'	'HIGH'	0
'SCIENTIFIC'	'HIGH'	-4
'SCIENTIFIC'	'HIGH'	5
'SCIENTIFIC'	'HIGH'	-1
'SCIENTIFIC'	'HIGH'	-9
'SCIENTIFIC'	'HIGH'	-5
'SCIENTIFIC'	'HIGH'	-6
'SCIENTIFIC'	'HIGH'	4
'SCIENTIFIC'	'HIGH'	-13
'SCIENTIFIC'	'HIGH'	-1
'SCIENTIFIC'	'HIGH'	-3
'SCIENTIFIC'	'HIGH'	-11
'SCIENTIFIC'	'HIGH'	-6
'SCIENTIFIC'	'HIGH'	-4
'SCIENTIFIC'	'LOW'	6
'SCIENTIFIC'	'LOW'	-5
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	-11
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	-5
'SCIENTIFIC'	'LOW'	-22
'SCIENTIFIC'	'LOW'	7
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	15
'SCIENTIFIC'	'LOW'	-6
'SCIENTIFIC'	'LOW'	9
'SCIENTIFIC'	'LOW'	-5
'NONE'	'HIGH'	-26
'NONE'	'HIGH'	-1
'NONE'	'HIGH'	22
'NONE'	'HIGH'	3
'NONE'	'HIGH'	-26
'NONE'	'HIGH'	4
'NONE'	'HIGH'	-21
'NONE'	'HIGH'	-19
'NONE'	'HIGH'	-12
'NONE'	'HIGH'	9
'NONE'	'HIGH'	-9
'NONE'	'HIGH'	-27
'NONE'	'HIGH'	-10
'NONE'	'HIGH'	-37
'NONE'	'HIGH'	0
'NONE'	'HIGH'	-10
'NONE'	'LOW'	-12
'NONE'	'LOW'	-4
'NONE'	'LOW'	13
'NONE'	'LOW'	-27
'NONE'	'LOW'	-7
'NONE'	'LOW'	-20
'NONE'	'LOW'	-4
'NONE'	'LOW'	-10
'NONE'	'LOW'	-3
'NONE'	'LOW'	-11
'NONE'	'LOW'	2
'NONE'	'LOW'	-9
'NONE'	'LOW'	20
'NONE'	'LOW'	9
'NONE'	'LOW'	-8
'NONE'	'LOW'	8
'NONE'	'LOW'	-6
'NONE'	'LOW'	6


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79509&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79509&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79509&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 1 seconds R Server 'George Udny Yule' @ 72.249.76.132

 ANOVA Model R ~ Exp * Inst names (Intercept) ExpLOW InstNONE InstSCIENTIFIC ExpLOW:InstNONE ExpLOW:InstSCIENTIFIC means 4.067 -22.125 -14.067 -11.011 28.625 30.993

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
R ~ Exp * Inst \tabularnewline
names & (Intercept) & ExpLOW & InstNONE & InstSCIENTIFIC & ExpLOW:InstNONE & ExpLOW:InstSCIENTIFIC \tabularnewline
means & 4.067 & -22.125 & -14.067 & -11.011 & 28.625 & 30.993 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79509&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]R ~ Exp * Inst[/C][/ROW]
[ROW][C]names[/C][C](Intercept)[/C][C]ExpLOW[/C][C]InstNONE[/C][C]InstSCIENTIFIC[/C][C]ExpLOW:InstNONE[/C][C]ExpLOW:InstSCIENTIFIC[/C][/ROW]
[ROW][C]means[/C][C]4.067[/C][C]-22.125[/C][C]-14.067[/C][C]-11.011[/C][C]28.625[/C][C]30.993[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79509&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79509&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 R ~ Exp * Inst names (Intercept) ExpLOW InstNONE InstSCIENTIFIC ExpLOW:InstNONE ExpLOW:InstSCIENTIFIC means 4.067 -22.125 -14.067 -11.011 28.625 30.993

 ANOVA Statistics Df Sum Sq Mean Sq F value Pr(>F) 1 Exp 1 165.945 165.945 1.042 0.31 Inst 1 295.635 147.817 0.928 0.399 Exp:Inst 1 4729.436 2364.718 14.844 0 Residuals 91 14496.242 159.299

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
& Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
& 1 &  &  &  &  \tabularnewline
Exp & 1 & 165.945 & 165.945 & 1.042 & 0.31 \tabularnewline
Inst & 1 & 295.635 & 147.817 & 0.928 & 0.399 \tabularnewline
Exp:Inst & 1 & 4729.436 & 2364.718 & 14.844 & 0 \tabularnewline
Residuals & 91 & 14496.242 & 159.299 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79509&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][/C][C]1[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Exp[/C][C]1[/C][C]165.945[/C][C]165.945[/C][C]1.042[/C][C]0.31[/C][/ROW]
[ROW][C]Inst[/C][C]1[/C][C]295.635[/C][C]147.817[/C][C]0.928[/C][C]0.399[/C][/ROW]
[ROW][C]Exp:Inst[/C][C]1[/C][C]4729.436[/C][C]2364.718[/C][C]14.844[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]91[/C][C]14496.242[/C][C]159.299[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79509&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79509&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) 1 Exp 1 165.945 165.945 1.042 0.31 Inst 1 295.635 147.817 0.928 0.399 Exp:Inst 1 4729.436 2364.718 14.844 0 Residuals 91 14496.242 159.299

 Tukey Honest Significant Difference Comparisons diff lwr upr p adj LOW-HIGH -2.616 -7.707 2.475 0.31 NONE-GOOD 1.124 -6.283 8.531 0.931 SCIENTIFIC-GOOD 4.169 -3.41 11.747 0.393 SCIENTIFIC-NONE 3.045 -4.423 10.513 0.597 LOW:GOOD-HIGH:GOOD -22.125 -35.142 -9.109 0 HIGH:NONE-HIGH:GOOD -14.067 -27.273 -0.861 0.03 LOW:NONE-HIGH:GOOD -7.567 -20.413 5.28 0.526 HIGH:SCIENTIFIC-HIGH:GOOD -11.011 -23.857 1.835 0.136 LOW:SCIENTIFIC-HIGH:GOOD -2.144 -16.068 11.78 0.998 HIGH:NONE-LOW:GOOD 8.059 -4.74 20.858 0.45 LOW:NONE-LOW:GOOD 14.559 2.132 26.986 0.012 HIGH:SCIENTIFIC-LOW:GOOD 11.114 -1.313 23.542 0.107 LOW:SCIENTIFIC-LOW:GOOD 19.982 6.444 33.52 0.001 LOW:NONE-HIGH:NONE 6.5 -6.125 19.125 0.666 HIGH:SCIENTIFIC-HIGH:NONE 3.056 -9.57 15.681 0.981 LOW:SCIENTIFIC-HIGH:NONE 11.923 -1.797 25.643 0.126 HIGH:SCIENTIFIC-LOW:NONE -3.444 -15.693 8.804 0.963 LOW:SCIENTIFIC-LOW:NONE 5.423 -7.951 18.797 0.845 LOW:SCIENTIFIC-HIGH:SCIENTIFIC 8.868 -4.507 22.242 0.391

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
& diff & lwr & upr & p adj \tabularnewline
LOW-HIGH & -2.616 & -7.707 & 2.475 & 0.31 \tabularnewline
NONE-GOOD & 1.124 & -6.283 & 8.531 & 0.931 \tabularnewline
SCIENTIFIC-GOOD & 4.169 & -3.41 & 11.747 & 0.393 \tabularnewline
SCIENTIFIC-NONE & 3.045 & -4.423 & 10.513 & 0.597 \tabularnewline
LOW:GOOD-HIGH:GOOD & -22.125 & -35.142 & -9.109 & 0 \tabularnewline
HIGH:NONE-HIGH:GOOD & -14.067 & -27.273 & -0.861 & 0.03 \tabularnewline
LOW:NONE-HIGH:GOOD & -7.567 & -20.413 & 5.28 & 0.526 \tabularnewline
HIGH:SCIENTIFIC-HIGH:GOOD & -11.011 & -23.857 & 1.835 & 0.136 \tabularnewline
LOW:SCIENTIFIC-HIGH:GOOD & -2.144 & -16.068 & 11.78 & 0.998 \tabularnewline
HIGH:NONE-LOW:GOOD & 8.059 & -4.74 & 20.858 & 0.45 \tabularnewline
LOW:NONE-LOW:GOOD & 14.559 & 2.132 & 26.986 & 0.012 \tabularnewline
HIGH:SCIENTIFIC-LOW:GOOD & 11.114 & -1.313 & 23.542 & 0.107 \tabularnewline
LOW:SCIENTIFIC-LOW:GOOD & 19.982 & 6.444 & 33.52 & 0.001 \tabularnewline
LOW:NONE-HIGH:NONE & 6.5 & -6.125 & 19.125 & 0.666 \tabularnewline
HIGH:SCIENTIFIC-HIGH:NONE & 3.056 & -9.57 & 15.681 & 0.981 \tabularnewline
LOW:SCIENTIFIC-HIGH:NONE & 11.923 & -1.797 & 25.643 & 0.126 \tabularnewline
HIGH:SCIENTIFIC-LOW:NONE & -3.444 & -15.693 & 8.804 & 0.963 \tabularnewline
LOW:SCIENTIFIC-LOW:NONE & 5.423 & -7.951 & 18.797 & 0.845 \tabularnewline
LOW:SCIENTIFIC-HIGH:SCIENTIFIC & 8.868 & -4.507 & 22.242 & 0.391 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79509&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C]LOW-HIGH[/C][C]-2.616[/C][C]-7.707[/C][C]2.475[/C][C]0.31[/C][/ROW]
[ROW][C]NONE-GOOD[/C][C]1.124[/C][C]-6.283[/C][C]8.531[/C][C]0.931[/C][/ROW]
[ROW][C]SCIENTIFIC-GOOD[/C][C]4.169[/C][C]-3.41[/C][C]11.747[/C][C]0.393[/C][/ROW]
[ROW][C]SCIENTIFIC-NONE[/C][C]3.045[/C][C]-4.423[/C][C]10.513[/C][C]0.597[/C][/ROW]
[ROW][C]LOW:GOOD-HIGH:GOOD[/C][C]-22.125[/C][C]-35.142[/C][C]-9.109[/C][C]0[/C][/ROW]
[ROW][C]HIGH:NONE-HIGH:GOOD[/C][C]-14.067[/C][C]-27.273[/C][C]-0.861[/C][C]0.03[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:GOOD[/C][C]-7.567[/C][C]-20.413[/C][C]5.28[/C][C]0.526[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:GOOD[/C][C]-11.011[/C][C]-23.857[/C][C]1.835[/C][C]0.136[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:GOOD[/C][C]-2.144[/C][C]-16.068[/C][C]11.78[/C][C]0.998[/C][/ROW]
[ROW][C]HIGH:NONE-LOW:GOOD[/C][C]8.059[/C][C]-4.74[/C][C]20.858[/C][C]0.45[/C][/ROW]
[ROW][C]LOW:NONE-LOW:GOOD[/C][C]14.559[/C][C]2.132[/C][C]26.986[/C][C]0.012[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:GOOD[/C][C]11.114[/C][C]-1.313[/C][C]23.542[/C][C]0.107[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:GOOD[/C][C]19.982[/C][C]6.444[/C][C]33.52[/C][C]0.001[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:NONE[/C][C]6.5[/C][C]-6.125[/C][C]19.125[/C][C]0.666[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:NONE[/C][C]3.056[/C][C]-9.57[/C][C]15.681[/C][C]0.981[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:NONE[/C][C]11.923[/C][C]-1.797[/C][C]25.643[/C][C]0.126[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:NONE[/C][C]-3.444[/C][C]-15.693[/C][C]8.804[/C][C]0.963[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:NONE[/C][C]5.423[/C][C]-7.951[/C][C]18.797[/C][C]0.845[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:SCIENTIFIC[/C][C]8.868[/C][C]-4.507[/C][C]22.242[/C][C]0.391[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79509&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79509&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 LOW-HIGH -2.616 -7.707 2.475 0.31 NONE-GOOD 1.124 -6.283 8.531 0.931 SCIENTIFIC-GOOD 4.169 -3.41 11.747 0.393 SCIENTIFIC-NONE 3.045 -4.423 10.513 0.597 LOW:GOOD-HIGH:GOOD -22.125 -35.142 -9.109 0 HIGH:NONE-HIGH:GOOD -14.067 -27.273 -0.861 0.03 LOW:NONE-HIGH:GOOD -7.567 -20.413 5.28 0.526 HIGH:SCIENTIFIC-HIGH:GOOD -11.011 -23.857 1.835 0.136 LOW:SCIENTIFIC-HIGH:GOOD -2.144 -16.068 11.78 0.998 HIGH:NONE-LOW:GOOD 8.059 -4.74 20.858 0.45 LOW:NONE-LOW:GOOD 14.559 2.132 26.986 0.012 HIGH:SCIENTIFIC-LOW:GOOD 11.114 -1.313 23.542 0.107 LOW:SCIENTIFIC-LOW:GOOD 19.982 6.444 33.52 0.001 LOW:NONE-HIGH:NONE 6.5 -6.125 19.125 0.666 HIGH:SCIENTIFIC-HIGH:NONE 3.056 -9.57 15.681 0.981 LOW:SCIENTIFIC-HIGH:NONE 11.923 -1.797 25.643 0.126 HIGH:SCIENTIFIC-LOW:NONE -3.444 -15.693 8.804 0.963 LOW:SCIENTIFIC-LOW:NONE 5.423 -7.951 18.797 0.845 LOW:SCIENTIFIC-HIGH:SCIENTIFIC 8.868 -4.507 22.242 0.391

 Levenes Test for Homogeneity of Variance Df F value Pr(>F) Group 5 1.731 0.135 91

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
& Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.731 & 0.135 \tabularnewline
& 91 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79509&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]1.731[/C][C]0.135[/C][/ROW]
[ROW][C] [/C][C]91[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79509&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79509&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 1.731 0.135 91

cat1 <- as.numeric(par1) #cat2<- as.numeric(par2) #cat3 <- as.numeric(par3)intercept<-as.logical(par4)x <- t(x)x1<-as.numeric(x[,cat1])f1<-as.character(x[,cat2])f2 <- as.character(x[,cat3])xdf<-data.frame(x1,f1, f2)(V1<-dimnames(y)[[1]][cat1])(V2<-dimnames(y)[[1]][cat2])(V3 <-dimnames(y)[[1]][cat3])mynames<- c(V1, V2, V3)xdf2<-xdfnames(xdf2)<-mynamesnames(xdf)<-c('R', 'A', 'B')mynames <- c(V1, V2, V3)if(intercept == FALSE)eval (substitute(lmout<-lm(xdf$R ~ xdf$A * xdf$B- 1, data = xdf), list(xdf=quote(xdf2),R=mynames[1],A=mynames[2],B=mynames[3]) ))else eval(substitute(lmout<-lm(xdf$R ~ xdf$A * xdf$B, data = xdf), list(xdf=quote(xdf2),R=mynames[1],A=mynames[2],B=mynames[3]) ))oldnames<-names(lmout$coeff)newnames<-gsub('xdf2\\$', '', oldnames)(names(lmout$coeff)<-newnames)(names(lmout$coefficients)<-newnames)load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'ANOVA Model', length(lmout$coefficients)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)callstr<-gsub('xdf2\\$', '',as.character(lmout$call$formula))callstr<-paste(callstr[2], callstr[1], callstr[3])a<-table.element(a,callstr ,length(lmout$coefficients)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, 'names',,TRUE)for(i in 1:length(lmout$coefficients)){a<-table.element(a, names(lmout$coefficients[i]),,FALSE)}a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, 'means',,TRUE)for(i in 1:length(lmout$coefficients)){a<-table.element(a, round(lmout$coefficients[i], digits=3),,FALSE)}a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable.tab')(aov.xdf<-aov(lmout) )(anova.xdf<-anova(lmout) )rownames(anova.xdf)<-gsub('xdf2\\$','',rownames(anova.xdf))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)for(i in 1 : length(rownames(anova.xdf))-1){a<-table.row.start(a)a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)a<-table.element(a, anova.xdf$Df[1],,FALSE)a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], digits=3),,FALSE)a<-table.row.end(a)}a<-table.row.start(a)a<-table.element(a, 'Residuals',,TRUE)a<-table.element(a, anova.xdf$'Df'[i+1],,FALSE)a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], 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(R ~ A + B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups',cex.axis=0.7 )dev.off()bitmap(file='designplot.png')xdf2 <- xdf # to preserve xdf make copy for functionnames(xdf2) <- c(V1, V2, V3)plot.design(xdf2, main='Design Plot of Group Means')dev.off()bitmap(file='interactionplot.png')interaction.plot(xdf$A, xdf$B, xdf\$R, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')dev.off()if(intercept==TRUE){thsd<-TukeyHSD(aov.xdf)names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))bitmap(file='TukeyHSDPlot.png')par(mai=c(1,1.5,1,1))layout(matrix(c(1,2,1,2,3,3,3,3), 2,4))plot(thsd, las=1)dev.off()}if(intercept==TRUE){ntables<-length(names(thsd))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(nt in 1:ntables){for(i in 1:length(rownames(thsd[[nt]]))){a<-table.row.start(a)a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)for(j in 1:4){a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)}a<-table.row.end(a)}} # end nta<-table.end(a)table.save(a,file='hsdtable.tab')}#end if hsd tablesif(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(lmout)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')