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Author's title

Author

*Unverified author*

R Software Module

Ian.Hollidayrwasp_Two Factor ANOVA -V4.wasp

Title produced by software

Variability

Date of computation

Tue, 30 Nov 2010 21:42:30 +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/30/t12911536679ryudt026ruityc.htm/, Retrieved Thu, 07 Dec 2023 04:47:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103831, Retrieved Thu, 07 Dec 2023 04:47:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

ANOVA, levene's test, Tukey's HSD

Estimated Impact

469

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Variability] [Two-Way ANOVA] [2010-11-30 21:42:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P     [Variability] [anova] [2010-12-01 18:26:17] [0f001550dea2fc4fb5273b1f5a571e75] 
-         [Variability] [Anova Boxplot ] [2010-12-02 11:37:34] [3bda7d0113b56426af4979274b798dbe] 
-         [Variability] [original box and ...] [2010-12-02 11:40:37] [404b7cc4dc7a1aee40b74eb017dcd509] 
-         [Variability] [anova test week 9] [2010-12-02 12:27:40] [a88d4f8d31dfea292b0820825eeec6b4] 
-         [Variability] [anova test week 9] [2010-12-02 12:27:40] [a88d4f8d31dfea292b0820825eeec6b4] 
-         [Variability] [anova test week 9] [2010-12-02 12:27:40] [a88d4f8d31dfea292b0820825eeec6b4] 
-         [Variability] [COMPENDIUM 9] [2010-12-02 12:38:22] [2736edfd04acceff7ef750b1b52381c2] 
-         [Variability] [COMPENDIUM 9] [2010-12-02 12:38:22] [2736edfd04acceff7ef750b1b52381c2] 
-         [Variability] [] [2010-12-02 12:42:52] [e41d04f9b27258a4b30e5e5545051fd7] 
-         [Variability] [] [2010-12-02 13:01:42] [74be16979710d4c4e7c6647856088456] 
-         [Variability] [compendium] [2010-12-02 13:20:46] [bbe2ba08a2e1004d231616e60eeea4d7] 
-         [Variability] [anova test of curry] [2010-12-02 13:24:46] [2265fa04dc9037ffed1746190cb362a2] 
-         [Variability] [Week 9 Anova 2] [2010-12-02 13:31:21] [dddf47df3158f3415096d83fcbb31970] 
-           [Variability] [] [2010-12-07 15:57:12] [19600d31edce75009224fbecf9086a65] 
-         [Variability] [] [2010-12-02 14:16:04] [2c73ce1a871fd05a9ff8be670c4acb3a] 
-         [Variability] [9] [2010-12-02 18:42:16] [1a8e34d31778cea87d7e7a201d42c24e] 
-   P     [Variability] [2 way anova] [2010-12-02 19:38:44] [74be16979710d4c4e7c6647856088456] 
-   P       [Variability] [compendium 9] [2010-12-06 01:33:17] [ea66f500a1c7f64f8e44100d9ad7d0a4] 
-   P       [Variability] [] [2010-12-07 12:04:13] [deecdb41704fb2bc07b9b59abf667938] 
-         [Variability] [] [2010-12-02 19:50:07] [5f3db3d90d126a95d54183950148004f] 
-    D    [Variability] [] [2010-12-02 21:33:30] [358781f0bd1d7f23f7c8aa2873c865a2] 
-         [Variability] [two way ANOVA] [2010-12-03 09:25:20] [4ff27dd7c583dd02fd8841b940d8c8a4] 
- RMPD    [] [] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456] 
-         [Variability] [2 way ANOVA curry...] [2010-12-03 12:36:52] [0aad37657179c4ab6867a73eb1b2180e] 
-         [Variability] [Comp 9 2-way ANOV...] [2010-12-03 13:02:33] [b3d3d2a4e3813ea6c4a04808e1fc1271] 
-         [Variability] [Part 2] [2010-12-03 13:33:50] [15d95c9569f1ac5858317a9687e82457] 
-         [Variability] [] [2010-12-03 13:33:52] [74be16979710d4c4e7c6647856088456] 
-         [Variability] [two-way ANOVA spi...] [2010-12-03 14:58:21] [74be16979710d4c4e7c6647856088456] 
-    D    [Variability] [W9 Compendium EX 1B] [2010-12-03 16:51:43] [56deace5afbbe22352c3841e29b79134] 
-    D    [Variability] [W9 Compendium Ex 1B] [2010-12-03 17:13:14] [56deace5afbbe22352c3841e29b79134] 
-         [Variability] [compendium 9 boxp...] [2010-12-03 17:47:37] [1592300573d920cdca8e2dce0d3bab21] 
-         [Variability] [week 9 compendium...] [2010-12-03 19:13:20] [88bba52b01540967ecde38774018061d] 
-           [Variability] [wek9] [2010-12-07 15:23:50] [74be16979710d4c4e7c6647856088456] 
-         [Variability] [Smoker/Non Smoker...] [2010-12-03 19:16:49] [05f6bac91e3f566f17ccf54f910765b8] 
-         [Variability] [spiciness VS type...] [2010-12-03 22:11:57] [cf42e4b21c34e98ab0a195af47af01df] 
-         [Variability] [my compendium week 9] [2010-12-04 15:00:52] [abe244594d47c647168999d9ae7a699b] 
-         [Variability] [] [2010-12-04 17:09:19] [ae8ba68bb93f8c963c36f4f8ef8e9f76] 
-           [Variability] [Ratings of spicin...] [2010-12-07 15:14:17] [48b6bddf3e494a4ea4b8c9bd6bc25768] 
-         [Variability] [curry anova] [2010-12-04 17:29:15] [05f6bac91e3f566f17ccf54f910765b8] 
-         [Variability] [compendium 9 week ] [2010-12-04 18:43:30] [791b6e9b5b89a59caaa2a08b67d5f6f0] 
-         [Variability] [Two-Way ANOVA] [2010-12-05 18:20:40] [a213e16b9aee3f49d2cb9e790c69a2a0] 
- R  D      [Variability] [BPVT & RAD Analysis] [2011-05-27 09:44:51] [f15c1d3d71c6e2d29ae45c04b0ae6886] 
- R  D      [Variability] [BPVT and RAD scores] [2011-05-31 09:20:50] [f15c1d3d71c6e2d29ae45c04b0ae6886] 
- RMPD    [] [anova wk09] [-0001-11-30 00:00:00] [920d86197c99e892f7cfc71aadebcde0] 
-         [Variability] [compendium 9] [2010-12-05 23:00:36] [ad05cf1a8cbb8345f8bf2af89f3d97f1] 
-         [Variability] [anova wk09] [2010-12-05 23:37:52] [920d86197c99e892f7cfc71aadebcde0] 
-         [Variability] [anova wk09] [2010-12-05 23:43:41] [920d86197c99e892f7cfc71aadebcde0] 
-    D      [Variability] [Smoker/non-smoker...] [2010-12-10 13:36:15] [920d86197c99e892f7cfc71aadebcde0] 

[Truncated]

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Dataseries X:

Download CSV

Histogram

Boxplots

4	'SMK'	'hot'
5	'SMK'	'hot'
3	'SMK'	'hot'
4	'SMK'	'hot'
5	'SMK'	'hot'
3	'SMK'	'hot'
7	'SMK'	'hot'
5	'SMK'	'hot'
6	'SMK'	'hot'
3	'SMK'	'hot'
2	'SMK'	'hot'
4	'SMK'	'hot'
5	'SMK'	'hot'
2	'SMK'	'hot'
3	'SMK'	'hot'
6	'SMK'	'hot'
4	'SMK'	'hot'
4	'SMK'	'hot'
6	'SMK'	'hot'
2	'SMK'	'hot'
3	'SMK'	'mild'
5	'SMK'	'mild'
4	'SMK'	'mild'
2	'SMK'	'mild'
7	'SMK'	'mild'
1	'SMK'	'mild'
4	'SMK'	'mild'
4	'SMK'	'mild'
7	'SMK'	'mild'
4	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
2	'SMK'	'mild'
5	'SMK'	'mild'
5	'SMK'	'mild'
3	'SMK'	'mild'
6	'SMK'	'mild'
2	'SMK'	'mild'
8	'NS'	'hot'
9	'NS'	'hot'
10	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
9	'NS'	'hot'
10	'NS'	'hot'
6	'NS'	'hot'
6	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
9	'NS'	'hot'
8	'NS'	'hot'
7	'NS'	'hot'
5	'NS'	'hot'
11	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
10	'NS'	'hot'
9	'NS'	'hot'
3	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
2	'NS'	'mild'
6	'NS'	'mild'
1	'NS'	'mild'
4	'NS'	'mild'
4	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
3	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
2	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
6	'NS'	'mild'
2	'NS'	'mild'

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	'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103831&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103831&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	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
xdf2$rate ~ xdf2$status * xdf2$curry
names	(Intercept)	xdf2$statusSMK	xdf2$currymild	xdf2$statusSMK:xdf2$currymild
means	8.1	-3.95	-4.45	4.1

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
xdf2$rate ~ xdf2$status * xdf2$curry \tabularnewline
names & (Intercept) & xdf2$statusSMK & xdf2$currymild & xdf2$statusSMK:xdf2$currymild \tabularnewline
means & 8.1 & -3.95 & -4.45 & 4.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103831&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]xdf2$rate ~ xdf2$status * xdf2$curry[/C][/ROW]
[ROW][C]names[/C][C](Intercept)[/C][C]xdf2$statusSMK[/C][C]xdf2$currymild[/C][C]xdf2$statusSMK:xdf2$currymild[/C][/ROW]
[ROW][C]means[/C][C]8.1[/C][C]-3.95[/C][C]-4.45[/C][C]4.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103831&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
xdf2$rate ~ xdf2$status * xdf2$curry
names	(Intercept)	xdf2$statusSMK	xdf2$currymild	xdf2$statusSMK:xdf2$currymild
means	8.1	-3.95	-4.45	4.1

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	1
xdf2$status	1	72.2	72.2	31.884	2.6976e-07
xdf2$curry	1	115.2	115.2	50.873	4.9375e-10
xdf2$status:xdf2$curry	1	84.05	84.05	37.117	4.2483e-08
Residuals	76	172.1	2.2645

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
xdf2$status & 1 & 72.2 & 72.2 & 31.884 & 2.6976e-07 \tabularnewline
xdf2$curry & 1 & 115.2 & 115.2 & 50.873 & 4.9375e-10 \tabularnewline
xdf2$status:xdf2$curry & 1 & 84.05 & 84.05 & 37.117 & 4.2483e-08 \tabularnewline
Residuals & 76 & 172.1 & 2.2645 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103831&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]xdf2$status[/C][C]1[/C][C]72.2[/C][C]72.2[/C][C]31.884[/C][C]2.6976e-07[/C][/ROW]
[ROW][C]xdf2$curry[/C][C]1[/C][C]115.2[/C][C]115.2[/C][C]50.873[/C][C]4.9375e-10[/C][/ROW]
[ROW][C]xdf2$status:xdf2$curry[/C][C]1[/C][C]84.05[/C][C]84.05[/C][C]37.117[/C][C]4.2483e-08[/C][/ROW]
[ROW][C]Residuals[/C][C]76[/C][C]172.1[/C][C]2.2645[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103831&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103831&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
xdf2$status	1	72.2	72.2	31.884	2.6976e-07
xdf2$curry	1	115.2	115.2	50.873	4.9375e-10
xdf2$status:xdf2$curry	1	84.05	84.05	37.117	4.2483e-08
Residuals	76	172.1	2.2645

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
SMK-NS	-1.9	-2.5702	-1.2298	2.6967e-07
mild-hot	-2.4	-3.0702	-1.7298	4.0268e-10
SMK:hot-NS:hot	-3.95	-5.2	-2.7	0
NS:mild-NS:hot	-4.45	-5.7	-3.2	0
SMK:mild-NS:hot	-4.3	-5.55	-3.05	0
NS:mild-SMK:hot	-0.5	-1.75	0.75	0.72023
SMK:mild-SMK:hot	-0.35	-1.6	0.9	0.88249
SMK:mild-NS:mild	0.15	-1.1	1.4	0.98907

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
SMK-NS & -1.9 & -2.5702 & -1.2298 & 2.6967e-07 \tabularnewline
mild-hot & -2.4 & -3.0702 & -1.7298 & 4.0268e-10 \tabularnewline
SMK:hot-NS:hot & -3.95 & -5.2 & -2.7 & 0 \tabularnewline
NS:mild-NS:hot & -4.45 & -5.7 & -3.2 & 0 \tabularnewline
SMK:mild-NS:hot & -4.3 & -5.55 & -3.05 & 0 \tabularnewline
NS:mild-SMK:hot & -0.5 & -1.75 & 0.75 & 0.72023 \tabularnewline
SMK:mild-SMK:hot & -0.35 & -1.6 & 0.9 & 0.88249 \tabularnewline
SMK:mild-NS:mild & 0.15 & -1.1 & 1.4 & 0.98907 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103831&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]SMK-NS[/C][C]-1.9[/C][C]-2.5702[/C][C]-1.2298[/C][C]2.6967e-07[/C][/ROW]
[ROW][C]mild-hot[/C][C]-2.4[/C][C]-3.0702[/C][C]-1.7298[/C][C]4.0268e-10[/C][/ROW]
[ROW][C]SMK:hot-NS:hot[/C][C]-3.95[/C][C]-5.2[/C][C]-2.7[/C][C]0[/C][/ROW]
[ROW][C]NS:mild-NS:hot[/C][C]-4.45[/C][C]-5.7[/C][C]-3.2[/C][C]0[/C][/ROW]
[ROW][C]SMK:mild-NS:hot[/C][C]-4.3[/C][C]-5.55[/C][C]-3.05[/C][C]0[/C][/ROW]
[ROW][C]NS:mild-SMK:hot[/C][C]-0.5[/C][C]-1.75[/C][C]0.75[/C][C]0.72023[/C][/ROW]
[ROW][C]SMK:mild-SMK:hot[/C][C]-0.35[/C][C]-1.6[/C][C]0.9[/C][C]0.88249[/C][/ROW]
[ROW][C]SMK:mild-NS:mild[/C][C]0.15[/C][C]-1.1[/C][C]1.4[/C][C]0.98907[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103831&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103831&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
SMK-NS	-1.9	-2.5702	-1.2298	2.6967e-07
mild-hot	-2.4	-3.0702	-1.7298	4.0268e-10
SMK:hot-NS:hot	-3.95	-5.2	-2.7	0
NS:mild-NS:hot	-4.45	-5.7	-3.2	0
SMK:mild-NS:hot	-4.3	-5.55	-3.05	0
NS:mild-SMK:hot	-0.5	-1.75	0.75	0.72023
SMK:mild-SMK:hot	-0.35	-1.6	0.9	0.88249
SMK:mild-NS:mild	0.15	-1.1	1.4	0.98907

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	3	0.24987	0.86119
	76

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.24987 & 0.86119 \tabularnewline
  & 76 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103831&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]3[/C][C]0.24987[/C][C]0.86119[/C][/ROW]
[ROW][C] [/C][C]76[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103831&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103831&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	3	0.24987	0.86119
	76

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

Parameters (R input):

par1 = 1 ; par2 = 2 ; par3 = 3 ; 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, signif(lmout$coefficients[i], digits=5),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
(aov.xdf<-aov(lmout) )
(anova.xdf<-anova(lmout) )
rownames(anova.xdf)<-gsub('xdf2$','',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$Df[1],,FALSE)
a<-table.element(a, signif(anova.xdf$'Sum Sq'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Mean Sq'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'F value'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Pr(>F)'[i], digits=5),,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$'Df'[i+1],,FALSE)
a<-table.element(a, signif(anova.xdf$'Sum Sq'[i+1], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Mean Sq'[i+1], digits=5),,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')
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')
layout(matrix(c(0,0,1,2,1,2,0,0,3,3,3,3), 2,6))
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,signif(thsd[[nt]][i,j], digits=5), 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,signif(lt.lmxdf[[i]][1], digits=5), 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