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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_STARS_Bullying_Study_alt.wasp
Title produced by softwareChi-Square Test
Date of computationMon, 21 Nov 2011 05:21:16 -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/2011/Nov/21/t1321872260raiv5noiusvv5hy.htm/, Retrieved Thu, 31 Oct 2024 23:00:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145693, Retrieved Thu, 31 Oct 2024 23:00:39 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [Bullying by Gender] [2009-11-23 19:30:44] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Chi Square Measure of Association- Free Statistics Software (Calculator)] [Bullying by Gende...] [2009-11-24 18:28:32] [b98453cac15ba1066b407e146608df68]
- R       [Chi Square Measure of Association- Free Statistics Software (Calculator)] [STARS Bullying Study] [2009-11-25 00:02:16] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD      [Chi-Square Test] [STARS Bullying Study] [2010-11-15 17:05:23] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R           [Chi-Square Test] [STARS Bullying Data] [2010-11-16 14:40:36] [98fd0e87c3eb04e0cc2efde01dbafab6]
-  MP           [Chi-Square Test] [chi2 Example - Ty...] [2011-11-14 11:58:51] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P               [Chi-Square Test] [Do children get b...] [2011-11-21 10:21:16] [b85a1df8c2fe1a89874e79d576ede57c] [Current]
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Dataseries X:
'g'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Physical'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Not_bul'	'Physical'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Physical'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Same'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Both'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Both'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Both'	'Both'	'Boys'
'b'	'Not_bul'	'Mental'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Differnt'	'Girls'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Mental'	'Not_bul'	'Boys'
'b'	'Rarely'	'Both'	'Differnt'	'Boys'
'b'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Same'	'Both'
'g'	'Often'	'Mental'	'Differnt'	'Both'
'b'	'Often'	'Both'	'Differnt'	'Both'
'g'	'Rarely'	'Physical'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Mental'	'Differnt'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Both'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Differnt'	'Girls'
'g'	'Often'	'Both'	'Differnt'	'Both'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Not_bul'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Both'	'Girls'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'b'	'Rarely'	'Both'	'Differnt'	'Boys'
'g'	'Rarely'	'Not_bul'	'Not_bul'	'Girls'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Often'	'Mental'	'Same'	'Boys'
'b'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Often'	'Physical'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Both'	'Both'	'Both'
'g'	'Rarely'	'Mental'	'Both'	'Both'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Both'
'g'	'Not_bul'	'Mental'	'Same'	'Both'
'g'	'Often'	'Physical'	'Differnt'	'Both'
'b'	'Often'	'Not_bul'	'Same'	'Boys'
'b'	'Often'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Mental'	'Same'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Not_bul'	'Both'
'g'	'Often'	'Both'	'Both'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Both'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Physical'	'Differnt'	'Boys'
'g'	'Often'	'Both'	'Same'	'Girls'
'g'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Often'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Both'	'Boys'
'b'	'Often'	'Not_bul'	'Both'	'Boys'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Not_bul'	'Both'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Both'	'Both'	'Boys'
'b'	'Rarely'	'Both'	'Both'	'Boys'
'b'	'Often'	'Physical'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Rarely'	'Both'	'Both'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Mental'	'Both'	'Both'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Both'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Same'	'Boys'
'g'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Both'	'Same'	'Boys'
'b'	'Often'	'Mental'	'Both'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Same'	'Boys'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Both'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Not_bul'	'Both'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Often'	'Mental'	'Not_bul'	'Both'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Often'	'Not_bul'	'Same'	'Both'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Rarely'	'Both'	'Both'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'g'	'Often'	'Both'	'Same'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145693&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145693&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145693&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Tabulation of Results
gender x which_year
BothDifferntNot_bulSame
b10233520
g11115231

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
gender  x  which_year \tabularnewline
  & Both & Differnt & Not_bul & Same \tabularnewline
b & 10 & 23 & 35 & 20 \tabularnewline
g & 11 & 11 & 52 & 31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145693&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]gender  x  which_year[/C][/ROW]
[ROW][C] [/C][C]Both[/C][C]Differnt[/C][C]Not_bul[/C][C]Same[/C][/ROW]
[C]b[/C][C]10[/C][C]23[/C][C]35[/C][C]20[/C][/ROW]
[C]g[/C][C]11[/C][C]11[/C][C]52[/C][C]31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145693&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145693&T=1

As an alternative you can also use a QR Code:  

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

Tabulation of Results
gender x which_year
BothDifferntNot_bulSame
b10233520
g11115231







Tabulation of Expected Results
gender x which_year
BothDifferntNot_bulSame
b9.5815.539.6723.25
g11.4218.547.3327.75

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
gender  x  which_year \tabularnewline
  & Both & Differnt & Not_bul & Same \tabularnewline
b & 9.58 & 15.5 & 39.67 & 23.25 \tabularnewline
g & 11.42 & 18.5 & 47.33 & 27.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145693&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]gender  x  which_year[/C][/ROW]
[ROW][C] [/C][C]Both[/C][C]Differnt[/C][C]Not_bul[/C][C]Same[/C][/ROW]
[C]b[/C][C]9.58[/C][C]15.5[/C][C]39.67[/C][C]23.25[/C][/ROW]
[C]g[/C][C]11.42[/C][C]18.5[/C][C]47.33[/C][C]27.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145693&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145693&T=2

As an alternative you can also use a QR Code:  

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

Tabulation of Expected Results
gender x which_year
BothDifferntNot_bulSame
b9.5815.539.6723.25
g11.4218.547.3327.75







Statistical Results
Pearson's Chi-squared test
Chi Square Statistic8.55
Degrees of Freedom3
P value0.04

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 8.55 \tabularnewline
Degrees of Freedom & 3 \tabularnewline
P value & 0.04 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145693&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test[/C][/ROW]
[ROW][C]Chi Square Statistic[/C][C]8.55[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]3[/C][/ROW]
[ROW][C]P value[/C][C]0.04[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145693&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145693&T=3

As an alternative you can also use a QR Code:  

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

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic8.55
Degrees of Freedom3
P value0.04



Parameters (Session):
par1 = 1 ; par2 = 4 ; par3 = Pearson Chi-Square ;
Parameters (R input):
par1 = 1 ; par2 = 4 ; par3 = Pearson Chi-Square ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
simulate.p.value=FALSE
if (par3 == 'Exact Pearson Chi Square by simulation') simulate.p.value=TRUE
x <- t(x)
(z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))
(table1 <- table(z[,cat1],z[,cat2]))
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, table1[nr, nc], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
(cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Statistical Results',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, cst$method, 2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Chi Square Statistic', 1, TRUE)
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
a<-table.row.end(a)
if(!simulate.p.value){
a<-table.row.start(a)
a<-table.element(a, 'Degrees of Freedom', 1, TRUE)
a<-table.element(a, cst$parameter, 1,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'P value', 1, TRUE)
a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')