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R Software Module

Ian.Hollidayrwasp_Two Factor ANOVA -V2.wasp

Title produced by software

Variability

Date of computation

Wed, 02 Jun 2010 09:11:16 +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/Jun/02/t1275469930yd9uiugjmo0s95l.htm/, Retrieved Sun, 09 Nov 2025 00:45:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76999, Retrieved Sun, 09 Nov 2025 00:45:51 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

452

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           [Variability] [Test 1] [2010-06-02 08:40:25] [7d07ebb7f3978280240b500f174a2af2]
- R  D            [Variability] [test 2] [2010-06-02 09:11:16] [8c86a5f0347705e3bc2cf4db7a37ce69] [Current]

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Dataseries X:

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Histogram

Boxplots

'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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	184.73.214.54 @ 184.73.214.54

\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 & 3 seconds \tabularnewline
R Server & 184.73.214.54 @ 184.73.214.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76999&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]184.73.214.54 @ 184.73.214.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76999&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76999&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	3 seconds
R Server	184.73.214.54 @ 184.73.214.54

ANOVA Model
rating ~ expectation * instruction
names	(Intercept)	expectationLOW	instructionNONE	instructionSCIENTIFIC	expectationLOW:instructionNONE	expectationLOW:instructionSCIENTIFIC
means	4.067	-22.125	-14.067	-11.011	28.188	30.993

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
rating ~ expectation * instruction \tabularnewline
names & (Intercept) & expectationLOW & instructionNONE & instructionSCIENTIFIC & expectationLOW:instructionNONE & expectationLOW:instructionSCIENTIFIC \tabularnewline
means & 4.067 & -22.125 & -14.067 & -11.011 & 28.188 & 30.993 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76999&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]rating ~ expectation * instruction[/C][/ROW]
[ROW][C]names[/C][C](Intercept)[/C][C]expectationLOW[/C][C]instructionNONE[/C][C]instructionSCIENTIFIC[/C][C]expectationLOW:instructionNONE[/C][C]expectationLOW:instructionSCIENTIFIC[/C][/ROW]
[ROW][C]means[/C][C]4.067[/C][C]-22.125[/C][C]-14.067[/C][C]-11.011[/C][C]28.188[/C][C]30.993[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76999&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76999&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
rating ~ expectation * instruction
names	(Intercept)	expectationLOW	instructionNONE	instructionSCIENTIFIC	expectationLOW:instructionNONE	expectationLOW:instructionSCIENTIFIC
means	4.067	-22.125	-14.067	-11.011	28.188	30.993

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	1
expectation	1	203.489	203.489	1.258	0.265
instruction	1	313.825	156.912	0.97	0.383
expectation:instruction	1	4630.996	2315.498	14.314	0
Residuals	89	14396.68	161.76

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
expectation & 1 & 203.489 & 203.489 & 1.258 & 0.265 \tabularnewline
instruction & 1 & 313.825 & 156.912 & 0.97 & 0.383 \tabularnewline
expectation:instruction & 1 & 4630.996 & 2315.498 & 14.314 & 0 \tabularnewline
Residuals & 89 & 14396.68 & 161.76 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76999&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]expectation[/C][C]1[/C][C]203.489[/C][C]203.489[/C][C]1.258[/C][C]0.265[/C][/ROW]
[ROW][C]instruction[/C][C]1[/C][C]313.825[/C][C]156.912[/C][C]0.97[/C][C]0.383[/C][/ROW]
[ROW][C]expectation:instruction[/C][C]1[/C][C]4630.996[/C][C]2315.498[/C][C]14.314[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]89[/C][C]14396.68[/C][C]161.76[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76999&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76999&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
expectation	1	203.489	203.489	1.258	0.265
instruction	1	313.825	156.912	0.97	0.383
expectation:instruction	1	4630.996	2315.498	14.314	0
Residuals	89	14396.68	161.76

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
LOW-HIGH	-2.929	-8.117	2.26	0.265
NONE-GOOD	0.627	-6.952	8.206	0.979
SCIENTIFIC-GOOD	4.134	-3.506	11.774	0.405
SCIENTIFIC-NONE	3.507	-4.133	11.146	0.52
LOW:GOOD-HIGH:GOOD	-22.125	-35.249	-9.002	0
HIGH:NONE-HIGH:GOOD	-14.067	-27.381	-0.753	0.032
LOW:NONE-HIGH:GOOD	-8.004	-21.318	5.31	0.502
HIGH:SCIENTIFIC-HIGH:GOOD	-11.011	-23.962	1.94	0.142
LOW:SCIENTIFIC-HIGH:GOOD	-2.144	-16.181	11.894	0.998
HIGH:NONE-LOW:GOOD	8.059	-4.845	20.962	0.459
LOW:NONE-LOW:GOOD	14.121	1.218	27.025	0.024
HIGH:SCIENTIFIC-LOW:GOOD	11.114	-1.414	23.643	0.112
LOW:SCIENTIFIC-LOW:GOOD	19.982	6.333	33.631	0.001
LOW:NONE-HIGH:NONE	6.063	-7.035	19.16	0.757
HIGH:SCIENTIFIC-HIGH:NONE	3.056	-9.673	15.784	0.982
LOW:SCIENTIFIC-HIGH:NONE	11.923	-1.91	25.756	0.132
HIGH:SCIENTIFIC-LOW:NONE	-3.007	-15.736	9.722	0.983
LOW:SCIENTIFIC-LOW:NONE	5.861	-7.972	19.693	0.819
LOW:SCIENTIFIC-HIGH:SCIENTIFIC	8.868	-4.616	22.351	0.4

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
LOW-HIGH & -2.929 & -8.117 & 2.26 & 0.265 \tabularnewline
NONE-GOOD & 0.627 & -6.952 & 8.206 & 0.979 \tabularnewline
SCIENTIFIC-GOOD & 4.134 & -3.506 & 11.774 & 0.405 \tabularnewline
SCIENTIFIC-NONE & 3.507 & -4.133 & 11.146 & 0.52 \tabularnewline
LOW:GOOD-HIGH:GOOD & -22.125 & -35.249 & -9.002 & 0 \tabularnewline
HIGH:NONE-HIGH:GOOD & -14.067 & -27.381 & -0.753 & 0.032 \tabularnewline
LOW:NONE-HIGH:GOOD & -8.004 & -21.318 & 5.31 & 0.502 \tabularnewline
HIGH:SCIENTIFIC-HIGH:GOOD & -11.011 & -23.962 & 1.94 & 0.142 \tabularnewline
LOW:SCIENTIFIC-HIGH:GOOD & -2.144 & -16.181 & 11.894 & 0.998 \tabularnewline
HIGH:NONE-LOW:GOOD & 8.059 & -4.845 & 20.962 & 0.459 \tabularnewline
LOW:NONE-LOW:GOOD & 14.121 & 1.218 & 27.025 & 0.024 \tabularnewline
HIGH:SCIENTIFIC-LOW:GOOD & 11.114 & -1.414 & 23.643 & 0.112 \tabularnewline
LOW:SCIENTIFIC-LOW:GOOD & 19.982 & 6.333 & 33.631 & 0.001 \tabularnewline
LOW:NONE-HIGH:NONE & 6.063 & -7.035 & 19.16 & 0.757 \tabularnewline
HIGH:SCIENTIFIC-HIGH:NONE & 3.056 & -9.673 & 15.784 & 0.982 \tabularnewline
LOW:SCIENTIFIC-HIGH:NONE & 11.923 & -1.91 & 25.756 & 0.132 \tabularnewline
HIGH:SCIENTIFIC-LOW:NONE & -3.007 & -15.736 & 9.722 & 0.983 \tabularnewline
LOW:SCIENTIFIC-LOW:NONE & 5.861 & -7.972 & 19.693 & 0.819 \tabularnewline
LOW:SCIENTIFIC-HIGH:SCIENTIFIC & 8.868 & -4.616 & 22.351 & 0.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76999&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]-2.929[/C][C]-8.117[/C][C]2.26[/C][C]0.265[/C][/ROW]
[ROW][C]NONE-GOOD[/C][C]0.627[/C][C]-6.952[/C][C]8.206[/C][C]0.979[/C][/ROW]
[ROW][C]SCIENTIFIC-GOOD[/C][C]4.134[/C][C]-3.506[/C][C]11.774[/C][C]0.405[/C][/ROW]
[ROW][C]SCIENTIFIC-NONE[/C][C]3.507[/C][C]-4.133[/C][C]11.146[/C][C]0.52[/C][/ROW]
[ROW][C]LOW:GOOD-HIGH:GOOD[/C][C]-22.125[/C][C]-35.249[/C][C]-9.002[/C][C]0[/C][/ROW]
[ROW][C]HIGH:NONE-HIGH:GOOD[/C][C]-14.067[/C][C]-27.381[/C][C]-0.753[/C][C]0.032[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:GOOD[/C][C]-8.004[/C][C]-21.318[/C][C]5.31[/C][C]0.502[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:GOOD[/C][C]-11.011[/C][C]-23.962[/C][C]1.94[/C][C]0.142[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:GOOD[/C][C]-2.144[/C][C]-16.181[/C][C]11.894[/C][C]0.998[/C][/ROW]
[ROW][C]HIGH:NONE-LOW:GOOD[/C][C]8.059[/C][C]-4.845[/C][C]20.962[/C][C]0.459[/C][/ROW]
[ROW][C]LOW:NONE-LOW:GOOD[/C][C]14.121[/C][C]1.218[/C][C]27.025[/C][C]0.024[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:GOOD[/C][C]11.114[/C][C]-1.414[/C][C]23.643[/C][C]0.112[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:GOOD[/C][C]19.982[/C][C]6.333[/C][C]33.631[/C][C]0.001[/C][/ROW]
[ROW][C]LOW:NONE-HIGH:NONE[/C][C]6.063[/C][C]-7.035[/C][C]19.16[/C][C]0.757[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-HIGH:NONE[/C][C]3.056[/C][C]-9.673[/C][C]15.784[/C][C]0.982[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:NONE[/C][C]11.923[/C][C]-1.91[/C][C]25.756[/C][C]0.132[/C][/ROW]
[ROW][C]HIGH:SCIENTIFIC-LOW:NONE[/C][C]-3.007[/C][C]-15.736[/C][C]9.722[/C][C]0.983[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-LOW:NONE[/C][C]5.861[/C][C]-7.972[/C][C]19.693[/C][C]0.819[/C][/ROW]
[ROW][C]LOW:SCIENTIFIC-HIGH:SCIENTIFIC[/C][C]8.868[/C][C]-4.616[/C][C]22.351[/C][C]0.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76999&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76999&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	-2.929	-8.117	2.26	0.265
NONE-GOOD	0.627	-6.952	8.206	0.979
SCIENTIFIC-GOOD	4.134	-3.506	11.774	0.405
SCIENTIFIC-NONE	3.507	-4.133	11.146	0.52
LOW:GOOD-HIGH:GOOD	-22.125	-35.249	-9.002	0
HIGH:NONE-HIGH:GOOD	-14.067	-27.381	-0.753	0.032
LOW:NONE-HIGH:GOOD	-8.004	-21.318	5.31	0.502
HIGH:SCIENTIFIC-HIGH:GOOD	-11.011	-23.962	1.94	0.142
LOW:SCIENTIFIC-HIGH:GOOD	-2.144	-16.181	11.894	0.998
HIGH:NONE-LOW:GOOD	8.059	-4.845	20.962	0.459
LOW:NONE-LOW:GOOD	14.121	1.218	27.025	0.024
HIGH:SCIENTIFIC-LOW:GOOD	11.114	-1.414	23.643	0.112
LOW:SCIENTIFIC-LOW:GOOD	19.982	6.333	33.631	0.001
LOW:NONE-HIGH:NONE	6.063	-7.035	19.16	0.757
HIGH:SCIENTIFIC-HIGH:NONE	3.056	-9.673	15.784	0.982
LOW:SCIENTIFIC-HIGH:NONE	11.923	-1.91	25.756	0.132
HIGH:SCIENTIFIC-LOW:NONE	-3.007	-15.736	9.722	0.983
LOW:SCIENTIFIC-LOW:NONE	5.861	-7.972	19.693	0.819
LOW:SCIENTIFIC-HIGH:SCIENTIFIC	8.868	-4.616	22.351	0.4

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	1.694	0.144
	89

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.694 & 0.144 \tabularnewline
  & 89 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76999&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]1.694[/C][C]0.144[/C][/ROW]
[ROW][C] [/C][C]89[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76999&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76999&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	1.694	0.144
	89

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