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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationSun, 16 Dec 2012 10:36:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/16/t13556724909y0ame0i9rmgs9a.htm/, Retrieved Fri, 09 May 2025 14:01:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200436, Retrieved Fri, 09 May 2025 14:01:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Workshop 6 1] [2012-11-10 10:48:52] [e31fe164d58995c48777312ee804d655]
- R  D  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Workshop 6 1] [2012-11-10 12:17:04] [e31fe164d58995c48777312ee804d655]
- R PD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Paper: deel 5 chi...] [2012-12-16 15:08:52] [e31fe164d58995c48777312ee804d655]
- R  D      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [paper deel 5 chi] [2012-12-16 15:13:41] [dbae308bdff61c0f4902cc85498d0d35]
- R P         [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [paper deel 5 chi 2] [2012-12-16 15:20:16] [dbae308bdff61c0f4902cc85498d0d35]
- RMPD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [paper deel 5 a] [2012-12-16 15:36:10] [7915dafcfdccff56a257085e1714b048] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'Treatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	1
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	0
4	'No'	'Treatment'	NA	'UsedStats'	'No'	'Yes'	0
4	'Yes'	'Treatment'	NA	'UsedStats'	'Yes'	'Yes'	1
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'Treatment'	NA	'UsedStats'	'Yes'	'Yes'	0
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	1
4	'Yes'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'Treatment'	NA	'UsedStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	1
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	1
4	'No'	'Treatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'Treatment'	NA	'UsedStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'Treatment'	NA	'NoStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'UsedStats'	'Yes'	'Yes'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	0
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'Treatment'	NA	'UsedStats'	'No'	'No'	1
4	'Yes'	'Treatment'	NA	'UsedStats'	'Yes'	'Yes'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'Yes'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'Treatment'	NA	'UsedStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'Yes'	'Treatment'	NA	'UsedStats'	'Yes'	'Yes'	0
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'Treatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'Treatment'	NA	'UsedStats'	'Yes'	'Yes'	1
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	0
4	'Yes'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'Treatment'	NA	'NoStats'	'No'	'Yes'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'UsedStats'	'No'	'Yes'	0
4	'No'	'Treatment'	NA	'UsedStats'	'Yes'	'No'	0
4	'No'	'Treatment'	NA	'NoStats'	'No'	'Yes'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'Yes'	'NoTreatment'	NA	'UsedStats'	'No'	'No'	0
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
4	'No'	'NoTreatment'	NA	'UsedStats'	'Yes'	'No'	1
4	'No'	'NoTreatment'	NA	'NoStats'	'No'	'Yes'	0
4	'Yes'	'NoTreatment'	NA	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'No'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	1
2	'Yes'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'Treatment'	'UsedStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'Yes'	1
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'UsedStats'	'No'	'No'	1
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'UsedStats'	'No'	'Yes'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'UsedStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'UsedStats'	'No'	'Yes'	0
2	'Yes'	NA	'Treatment'	'UsedStats'	'No'	'Yes'	0
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'UsedStats'	'Yes'	'No'	0
2	'No'	NA	'Treatment'	'UsedStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	1
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	0
2	'No'	NA	'Treatment'	'UsedStats'	'No'	'No'	1
2	'No'	NA	'Treatment'	'NoStats'	'No'	'No'	1
2	'Yes'	NA	'NoTreatment'	'NoStats'	'No'	'No'	1
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'Yes'	0
2	'No'	NA	'NoTreatment'	'NoStats'	'No'	'No'	0
2	'Yes'	NA	'NoTreatment'	'UsedStats'	'Yes'	'No'	1
2	'Yes'	NA	'NoTreatment'	'UsedStats'	'Yes'	'Yes'	1
2	'Yes'	NA	'NoTreatment'	'UsedStats'	'No'	'No'	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200436&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200436&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200436&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
Weeks ~ UseLimit
means3.1922.96

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Weeks  ~  UseLimit \tabularnewline
means & 3.192 & 2.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200436&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Weeks  ~  UseLimit[/C][/ROW]
[ROW][C]means[/C][C]3.192[/C][C]2.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200436&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200436&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Model
Weeks ~ UseLimit
means3.1922.96






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
UseLimit21497.926748.963758.5760
Residuals152150.0740.987 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
UseLimit & 2 & 1497.926 & 748.963 & 758.576 & 0 \tabularnewline
Residuals & 152 & 150.074 & 0.987 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200436&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]UseLimit[/C][C]2[/C][C]1497.926[/C][C]748.963[/C][C]758.576[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]152[/C][C]150.074[/C][C]0.987[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200436&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200436&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
UseLimit21497.926748.963758.5760
Residuals152150.0740.987






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200436&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200436&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200436&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.7930.374
152 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.793 & 0.374 \tabularnewline
  & 152 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200436&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]1[/C][C]0.793[/C][C]0.374[/C][/ROW]
[ROW][C] [/C][C]152[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200436&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200436&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.7930.374
152


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
R code (references can be found in the software module):
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')