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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_chi_squared_tests.wasp
Title produced by softwareChi-Squared and McNemar Tests
Date of computationThu, 25 Nov 2010 12:35:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/25/t12906890099klzeu8fzq6i4vh.htm/, Retrieved Thu, 28 Mar 2024 16:51:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100915, Retrieved Thu, 28 Mar 2024 16:51:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Chi-Squared and McNemar Tests] [] [2010-11-23 15:32:07] [055a14fb8042f7ec27c73c5dfc3bfa50]
- R  D    [Chi-Squared and McNemar Tests] [connected vs Sepa...] [2010-11-25 12:35:36] [8690b0a5633f6ac5ed8a33b8894b072f] [Current]
-           [Chi-Squared and McNemar Tests] [] [2010-11-25 19:02:50] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
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Dataseries X:
A'	'A'
'A'	'C'
'D'	'B'
'D'	'C'
'B'	'A'
'B'	'D'
'A'	'D'
'B'	'B'
'B'	'B'
'A'	'A'
'A'	'D'
'B'	'B'
'A'	'B'
'A'	'A'
'C'	'A'
'C'	'C'
'B'	'C'
'A'	'A'
'A'	'A'
'C'	'C'
'C'	'C'
'D'	'D'
'A'	'A'
'A'	'A'
'A'	'C'
'A'	'C'
'B'	'B'
'C'	'A'
'C'	'C'
'B'	'C'
'D'	'D'
'D'	'C'
'A'	'D'
'B'	'A'
'B'	'D'
'C'	'C'
'D'	'D'
'B'	'C'
'D'	'D'
'B'	'C'
'A'	'C'
'B'	'C'
'A'	'C'
'B'	'C'
'A'	'D'
'A'	'B'
'A'	'A'
'C'	'B'
'B'	'A'
'A'	'C'
'C'	'A'
'C'	'D'
'C'	'C'
'B'	'A'
'C'	'C'
'A'	'C'
'A'	'B'
'D'	'B'
'A'	'B'
'B'	'B'
'D'	'D'
'A'	'B'
'B'	'B'
'D'	'B'
'B'	'D'
'B'	'A'
'B'	'B'
'D'	'D'
'A'	'A'
'B'	'A'
'A'	'B'
'D'	'A'
'B'	'A'
'A'	'A'
'B'	'D'
'A'	'D'
'A'	'A'
'B'	'D'
'D'	'D'
'A'	'D'
'C'	'B'
'A'	'A'
'B'	'A'
'A'	'C'
'C'	'B'
'C'	'D'
'A'	'A'
'C'	'B'
'D'	'C'
'C'	'C'
'D'	'B'
'B'	'C'
'B'	'A'
'C'	'D'
'D'	'D'
'A'	'B'
'A'	'B'
'B'	'D'
'A'	'B'
'C'	'B'
'A'	'B'
'A'	'B'
'B'	'A'
'C'	'D'
'C'	'A'
'A'	'C'
'A'	'B'
'A'	'A'
'B'	'B'
'A'	'A'
'D'	'B'
'D'	'C'
'C'	'A'
'C'	'C'
'A'	'B'
'A'	'C'
'C'	'A'
'B'	'A'
'C'	'B'
'A'	'B'
'C'	'A'
'D'	'D'
'A'	'A'
'A'	'A'
'C'	'D'
'D'	'C'
'A'	'C'
'A'	'A'
'C'	'B'
'B'	'C'
'C'	'C'
'D'	'C'
'A'	'A'
'D'	'D'
'A'	'A'
'C'	'D'
'D'	'D'
'B'	'B'
'D'	'B'
'B'	'B'
'D'	'B'
'C'	'B'
'D'	'B'
'D'	'B'
'D'	'D'
'A'	'D'
'C'	'D'
'B'	'B'
'C'	'D'
'B'	'C'
'A'	'A'
'A'	'A'
'B'	'A'
'B'	'A'
'B'	'B'
'C'	'D'
'B'	'C'
'C'	'A'
'C'	'B'
'B'	'C'
'C'	'B'
'B'	'B'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100915&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100915&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100915&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'George Udny Yule' @ 72.249.76.132



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
R code (references can be found in the software module):
library(vcd)
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
simulate.p.value=FALSE
if (par3 == 'Exact Pearson Chi-Squared 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])
bitmap(file='pic1.png')
assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T)
dev.off()
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) )
if (par3 == 'McNemar Chi-Squared') {
(cst <- mcnemar.test(table1))
}
if (par3 != 'McNemar Chi-Squared') {
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')