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Author

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R Software Module

Ian.Hollidayrwasp_Two Factor ANOVA -V2.wasp

Title produced by software

Variability

Date of computation

Mon, 31 May 2010 11:11:24 +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/May/31/t12753043271til1rc5q9f18bg.htm/, Retrieved Wed, 11 Jun 2025 06:17:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76732, Retrieved Wed, 11 Jun 2025 06:17:10 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

307

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  D          [Variability] [Trimmed 10%] [2010-05-31 11:11:24] [793acd13badf53a5cb4eee3c35e3c9ae] [Current]

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Dataseries X:

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Histogram

Boxplots

'NONE'	'HIGH'	-26
'NONE'	'HIGH'	-26
'GOOD'	'LOW'	-25
'GOOD'	'LOW'	-24
'GOOD'	'LOW'	-24
'SCIENTIFIC'	'HIGH'	-24
'SCIENTIFIC'	'HIGH'	-24
'GOOD'	'LOW'	-23
'GOOD'	'LOW'	-23
'GOOD'	'HIGH'	-22
'GOOD'	'LOW'	-22
'GOOD'	'LOW'	-22
'GOOD'	'LOW'	-22
'SCIENTIFIC'	'LOW'	-22
'NONE'	'HIGH'	-21
'GOOD'	'LOW'	-20
'NONE'	'LOW'	-20
'GOOD'	'LOW'	-19
'SCIENTIFIC'	'HIGH'	-19
'NONE'	'HIGH'	-19
'GOOD'	'LOW'	-17
'GOOD'	'HIGH'	-16
'GOOD'	'HIGH'	-13
'SCIENTIFIC'	'HIGH'	-13
'NONE'	'HIGH'	-12
'NONE'	'LOW'	-12
'SCIENTIFIC'	'HIGH'	-11
'SCIENTIFIC'	'LOW'	-11
'NONE'	'LOW'	-11
'GOOD'	'LOW'	-10
'NONE'	'HIGH'	-10
'NONE'	'HIGH'	-10
'NONE'	'LOW'	-10
'SCIENTIFIC'	'HIGH'	-9
'NONE'	'HIGH'	-9
'NONE'	'LOW'	-9
'GOOD'	'LOW'	-8
'NONE'	'LOW'	-8
'NONE'	'LOW'	-7
'GOOD'	'HIGH'	-6
'GOOD'	'HIGH'	-6
'SCIENTIFIC'	'HIGH'	-6
'SCIENTIFIC'	'HIGH'	-6
'SCIENTIFIC'	'LOW'	-6
'NONE'	'LOW'	-6
'SCIENTIFIC'	'HIGH'	-5
'SCIENTIFIC'	'LOW'	-5
'SCIENTIFIC'	'LOW'	-5
'SCIENTIFIC'	'LOW'	-5
'SCIENTIFIC'	'HIGH'	-4
'SCIENTIFIC'	'HIGH'	-4
'SCIENTIFIC'	'HIGH'	-4
'NONE'	'LOW'	-4
'NONE'	'LOW'	-4
'SCIENTIFIC'	'HIGH'	-3
'NONE'	'LOW'	-3
'GOOD'	'HIGH'	-2
'GOOD'	'LOW'	-2
'SCIENTIFIC'	'HIGH'	-1
'SCIENTIFIC'	'HIGH'	-1
'NONE'	'HIGH'	-1
'GOOD'	'HIGH'	0
'SCIENTIFIC'	'HIGH'	0
'NONE'	'HIGH'	0
'NONE'	'LOW'	2
'NONE'	'HIGH'	3
'GOOD'	'HIGH'	4
'SCIENTIFIC'	'HIGH'	4
'NONE'	'HIGH'	4
'GOOD'	'HIGH'	5
'SCIENTIFIC'	'HIGH'	5
'GOOD'	'HIGH'	6
'SCIENTIFIC'	'LOW'	6
'NONE'	'LOW'	6
'SCIENTIFIC'	'LOW'	7
'NONE'	'LOW'	8
'SCIENTIFIC'	'LOW'	9
'NONE'	'HIGH'	9
'NONE'	'LOW'	9
'GOOD'	'HIGH'	11
'GOOD'	'LOW'	12
'NONE'	'LOW'	13
'GOOD'	'HIGH'	14
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	14
'SCIENTIFIC'	'LOW'	15

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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76732&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76732&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76732&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	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
R ~ Exp * Inst
names	(Intercept)	ExpLOW	InstNONE	InstSCIENTIFIC	ExpLOW:InstNONE	ExpLOW:InstSCIENTIFIC
means	-2.083	-14.517	-6.994	-4.861	20.094	23.384

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
R ~ Exp * Inst \tabularnewline
names & (Intercept) & ExpLOW & InstNONE & InstSCIENTIFIC & ExpLOW:InstNONE & ExpLOW:InstSCIENTIFIC \tabularnewline
means & -2.083 & -14.517 & -6.994 & -4.861 & 20.094 & 23.384 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76732&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]-2.083[/C][C]-14.517[/C][C]-6.994[/C][C]-4.861[/C][C]20.094[/C][C]23.384[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76732&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76732&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	-2.083	-14.517	-6.994	-4.861	20.094	23.384

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	1
Exp	1	0.374	0.374	0.004	0.953
Inst	1	699.854	349.927	3.33	0.041
Exp:Inst	1	2216.695	1108.348	10.548	0
Residuals	81	8511.307	105.078

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Exp & 1 & 0.374 & 0.374 & 0.004 & 0.953 \tabularnewline
Inst & 1 & 699.854 & 349.927 & 3.33 & 0.041 \tabularnewline
Exp:Inst & 1 & 2216.695 & 1108.348 & 10.548 & 0 \tabularnewline
Residuals & 81 & 8511.307 & 105.078 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76732&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]0.374[/C][C]0.374[/C][C]0.004[/C][C]0.953[/C][/ROW]
[ROW][C]Inst[/C][C]1[/C][C]699.854[/C][C]349.927[/C][C]3.33[/C][C]0.041[/C][/ROW]
[ROW][C]Exp:Inst[/C][C]1[/C][C]2216.695[/C][C]1108.348[/C][C]10.548[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]81[/C][C]8511.307[/C][C]105.078[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76732&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76732&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	0.374	0.374	0.004	0.953
Inst	1	699.854	349.927	3.33	0.041
Exp:Inst	1	2216.695	1108.348	10.548	0
Residuals	81	8511.307	105.078

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
LOW-HIGH	-0.131	-4.505	4.243	0.953
NONE-GOOD	4.148	-2.398	10.693	0.29
SCIENTIFIC-GOOD	6.904	0.462	13.347	0.033
SCIENTIFIC-NONE	2.757	-3.566	9.08	0.553
LOW:GOOD-HIGH:GOOD	-14.517	-26.106	-2.928	0.006
HIGH:NONE-HIGH:GOOD	-6.994	-18.972	4.985	0.533
LOW:NONE-HIGH:GOOD	-1.417	-12.844	10.01	0.999
HIGH:SCIENTIFIC-HIGH:GOOD	-4.861	-16.013	6.29	0.799
LOW:SCIENTIFIC-HIGH:GOOD	4.006	-7.972	15.985	0.924
HIGH:NONE-LOW:GOOD	7.523	-3.816	18.862	0.388
LOW:NONE-LOW:GOOD	13.1	2.346	23.854	0.008
HIGH:SCIENTIFIC-LOW:GOOD	9.656	-0.805	20.117	0.088
LOW:SCIENTIFIC-LOW:GOOD	18.523	7.184	29.862	0
LOW:NONE-HIGH:NONE	5.577	-5.596	16.75	0.692
HIGH:SCIENTIFIC-HIGH:NONE	2.132	-8.759	13.024	0.993
LOW:SCIENTIFIC-HIGH:NONE	11	-0.737	22.737	0.079
HIGH:SCIENTIFIC-LOW:NONE	-3.444	-13.726	6.837	0.924
LOW:SCIENTIFIC-LOW:NONE	5.423	-5.75	16.596	0.717
LOW:SCIENTIFIC-HIGH:SCIENTIFIC	8.868	-2.024	19.759	0.177

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
LOW-HIGH & -0.131 & -4.505 & 4.243 & 0.953 \tabularnewline
NONE-GOOD & 4.148 & -2.398 & 10.693 & 0.29 \tabularnewline
SCIENTIFIC-GOOD & 6.904 & 0.462 & 13.347 & 0.033 \tabularnewline
SCIENTIFIC-NONE & 2.757 & -3.566 & 9.08 & 0.553 \tabularnewline
LOW:GOOD-HIGH:GOOD & -14.517 & -26.106 & -2.928 & 0.006 \tabularnewline
HIGH:NONE-HIGH:GOOD & -6.994 & -18.972 & 4.985 & 0.533 \tabularnewline
LOW:NONE-HIGH:GOOD & -1.417 & -12.844 & 10.01 & 0.999 \tabularnewline
HIGH:SCIENTIFIC-HIGH:GOOD & -4.861 & -16.013 & 6.29 & 0.799 \tabularnewline
LOW:SCIENTIFIC-HIGH:GOOD & 4.006 & -7.972 & 15.985 & 0.924 \tabularnewline
HIGH:NONE-LOW:GOOD & 7.523 & -3.816 & 18.862 & 0.388 \tabularnewline
LOW:NONE-LOW:GOOD & 13.1 & 2.346 & 23.854 & 0.008 \tabularnewline
HIGH:SCIENTIFIC-LOW:GOOD & 9.656 & -0.805 & 20.117 & 0.088 \tabularnewline
LOW:SCIENTIFIC-LOW:GOOD & 18.523 & 7.184 & 29.862 & 0 \tabularnewline
LOW:NONE-HIGH:NONE & 5.577 & -5.596 & 16.75 & 0.692 \tabularnewline
HIGH:SCIENTIFIC-HIGH:NONE & 2.132 & -8.759 & 13.024 & 0.993 \tabularnewline
LOW:SCIENTIFIC-HIGH:NONE & 11 & -0.737 & 22.737 & 0.079 \tabularnewline
HIGH:SCIENTIFIC-LOW:NONE & -3.444 & -13.726 & 6.837 & 0.924 \tabularnewline
LOW:SCIENTIFIC-LOW:NONE & 5.423 & -5.75 & 16.596 & 0.717 \tabularnewline
LOW:SCIENTIFIC-HIGH:SCIENTIFIC & 8.868 & -2.024 & 19.759 & 0.177 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76732&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]LOW-HIGH[/C][C]-0.131[/C][C]-4.505[/C][C]4.243[/C][C]0.953[/C][/ROW]
[ROW][C]NONE-GOOD[/C][C]4.148[/C][C]-2.398[/C][C]10.693[/C][C]0.29[/C][/ROW]
[ROW][C]SCIENTIFIC-GOOD[/C][C]6.904[/C][C]0.462[/C][C]13.347[/C][C]0.033[/C][/ROW]
[ROW][C]SCIENTIFIC-NONE[/C][C]2.757[/C][C]-3.566[/C][C]9.08[/C][C]0.553[/C][/ROW]
[ROW][C]LOW:GOOD-HIGH:GOOD[/C][C]-14.517[/C][C]-26.106[/C][C]-2.928[/C][C]0.006[/C][/ROW]
[ROW][C]HIGH:NONE-HIGH:GOOD[/C][C]-6.994[/C][C]-18.972[/C][C]4.985[/C][C]0.533[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:GOOD[/C][C]-1.417[/C][C]-12.844[/C][C]10.01[/C][C]0.999[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:GOOD[/C][C]-4.861[/C][C]-16.013[/C][C]6.29[/C][C]0.799[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:GOOD[/C][C]4.006[/C][C]-7.972[/C][C]15.985[/C][C]0.924[/C][/ROW]
[ROW][C]HIGH:NONE-LOW:GOOD[/C][C]7.523[/C][C]-3.816[/C][C]18.862[/C][C]0.388[/C][/ROW]
[ROW][C]LOW:NONE-LOW:GOOD[/C][C]13.1[/C][C]2.346[/C][C]23.854[/C][C]0.008[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:GOOD[/C][C]9.656[/C][C]-0.805[/C][C]20.117[/C][C]0.088[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:GOOD[/C][C]18.523[/C][C]7.184[/C][C]29.862[/C][C]0[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:NONE[/C][C]5.577[/C][C]-5.596[/C][C]16.75[/C][C]0.692[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:NONE[/C][C]2.132[/C][C]-8.759[/C][C]13.024[/C][C]0.993[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:NONE[/C][C]11[/C][C]-0.737[/C][C]22.737[/C][C]0.079[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:NONE[/C][C]-3.444[/C][C]-13.726[/C][C]6.837[/C][C]0.924[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:NONE[/C][C]5.423[/C][C]-5.75[/C][C]16.596[/C][C]0.717[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:SCIENTIFIC[/C][C]8.868[/C][C]-2.024[/C][C]19.759[/C][C]0.177[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76732&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76732&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	-0.131	-4.505	4.243	0.953
NONE-GOOD	4.148	-2.398	10.693	0.29
SCIENTIFIC-GOOD	6.904	0.462	13.347	0.033
SCIENTIFIC-NONE	2.757	-3.566	9.08	0.553
LOW:GOOD-HIGH:GOOD	-14.517	-26.106	-2.928	0.006
HIGH:NONE-HIGH:GOOD	-6.994	-18.972	4.985	0.533
LOW:NONE-HIGH:GOOD	-1.417	-12.844	10.01	0.999
HIGH:SCIENTIFIC-HIGH:GOOD	-4.861	-16.013	6.29	0.799
LOW:SCIENTIFIC-HIGH:GOOD	4.006	-7.972	15.985	0.924
HIGH:NONE-LOW:GOOD	7.523	-3.816	18.862	0.388
LOW:NONE-LOW:GOOD	13.1	2.346	23.854	0.008
HIGH:SCIENTIFIC-LOW:GOOD	9.656	-0.805	20.117	0.088
LOW:SCIENTIFIC-LOW:GOOD	18.523	7.184	29.862	0
LOW:NONE-HIGH:NONE	5.577	-5.596	16.75	0.692
HIGH:SCIENTIFIC-HIGH:NONE	2.132	-8.759	13.024	0.993
LOW:SCIENTIFIC-HIGH:NONE	11	-0.737	22.737	0.079
HIGH:SCIENTIFIC-LOW:NONE	-3.444	-13.726	6.837	0.924
LOW:SCIENTIFIC-LOW:NONE	5.423	-5.75	16.596	0.717
LOW:SCIENTIFIC-HIGH:SCIENTIFIC	8.868	-2.024	19.759	0.177

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	0.718	0.612
	81

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 0.718 & 0.612 \tabularnewline
  & 81 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76732&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]0.718[/C][C]0.612[/C][/ROW]
[ROW][C] [/C][C]81[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76732&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76732&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	0.718	0.612
	81

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 3 ; par2 = 2 ; par3 = 1 ; par4 = TRUE ;

Parameters (R input):

par1 = 3 ; par2 = 2 ; par3 = 1 ; par4 = TRUE ;

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

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<-xdf
names(xdf2)<-mynames
names(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 function
names(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 nt
a<-table.end(a)
table.save(a,file='hsdtable.tab')
}#end if hsd tables
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(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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code