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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 computationThu, 17 Nov 2011 08:36:47 -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/17/t1321537019tq6wgz51g01mtuv.htm/, Retrieved Thu, 28 Mar 2024 22:42:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=144578, Retrieved Thu, 28 Mar 2024 22:42:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
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] [] [2011-11-17 13:36:47] [10859d22281cca92ea91c7e9bff5476e] [Current]
-                     [Chi-Square Test] [] [2011-11-17 13:38:14] [221b3b4216f0c3837d81a9a9f89ff273]
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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 time2 seconds
R Server'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144578&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144578&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







Tabulation of Results
gender x how_often_bullied
Not_bulOftenRarely
b342430
g532824

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
gender  x  how_often_bullied \tabularnewline
  & Not_bul & Often & Rarely \tabularnewline
b & 34 & 24 & 30 \tabularnewline
g & 53 & 28 & 24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144578&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]gender  x  how_often_bullied[/C][/ROW]
[ROW][C] [/C][C]Not_bul[/C][C]Often[/C][C]Rarely[/C][/ROW]
[C]b[/C][C]34[/C][C]24[/C][C]30[/C][/ROW]
[C]g[/C][C]53[/C][C]28[/C][C]24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144578&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 how_often_bullied
Not_bulOftenRarely
b342430
g532824







Tabulation of Expected Results
gender x how_often_bullied
Not_bulOftenRarely
b39.6723.7124.62
g47.3328.2929.38

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
gender  x  how_often_bullied \tabularnewline
  & Not_bul & Often & Rarely \tabularnewline
b & 39.67 & 23.71 & 24.62 \tabularnewline
g & 47.33 & 28.29 & 29.38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144578&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]gender  x  how_often_bullied[/C][/ROW]
[ROW][C] [/C][C]Not_bul[/C][C]Often[/C][C]Rarely[/C][/ROW]
[C]b[/C][C]39.67[/C][C]23.71[/C][C]24.62[/C][/ROW]
[C]g[/C][C]47.33[/C][C]28.29[/C][C]29.38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144578&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144578&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 how_often_bullied
Not_bulOftenRarely
b39.6723.7124.62
g47.3328.2929.38







Statistical Results
Pearson's Chi-squared test
Chi Square Statistic3.65
Degrees of Freedom2
P value0.16

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 3.65 \tabularnewline
Degrees of Freedom & 2 \tabularnewline
P value & 0.16 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144578&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]3.65[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]2[/C][/ROW]
[ROW][C]P value[/C][C]0.16[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144578&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144578&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 Statistic3.65
Degrees of Freedom2
P value0.16



Parameters (Session):
par1 = 1 ; par2 = 5 ; par3 = Pearson Chi-Square ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; 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')