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Description of Statistical Computation

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 computationWed, 24 Nov 2010 09:25:41 +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/24/t12905907063lmat1yalfhnfq1.htm/, Retrieved Fri, 03 May 2024 05:53:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=99763, Retrieved Fri, 03 May 2024 05:53:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Chi-Squared and McNemar Tests] [Workshop 6 Hapine...] [2010-11-24 09:25:41] [44b139cd0a72f547e24abd0161061bfd] [Current]
-    D    [Chi-Squared and McNemar Tests] [Workshop 6 Hapine...] [2010-11-24 09:50:37] [38afc57aa6474689f791e00be1754a89]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
Happiness	Depression
'B'	'B'
'A'	'C'
'D'	'A'
'D'	'B'
'A'	'A'
'A'	'B'
'B'	'A'
'B'	'C'
'B'	'D'
'B'	'B'
'A'	'D'
'A'	'D'
'D'	'A'
'A'	'A'
'A'	'D'
'B'	'A'
'B'	'A'
'A'	'C'
'B'	'D'
'A'	'B'
'A'	'D'
'D'	'A'
'B'	'B'
'D'	'A'
'A'	'C'
'D'	'D'
'A'	'C'
'B'	'A'
'B'	'A'
'D'	'B'
'A'	'D'
'C'	'A'
'A'	'D'
'B'	'C'
'B'	'B'
'A'	'D'
'D'	'A'
'B'	'B'
'A'	'D'
'C'	'D'
'B'	'D'
'A'	'A'
'A'	'D'
'D'	'A'
'D'	'C'
'D'	'B'
'B'	'D'
'B'	'C'
'A'	'A'
'C'	'C'
'A'	'D'
'B'	'A'
'D'	'A'
'D'	'A'
'D'	'C'
'B'	'B'
'A'	'B'
'B'	'D'
'D'	'D'
'D'	'A'
'D'	'A'
'C'	'B'
'D'	'B'
'B'	'A'
'B'	'B'
'D'	'C'
'D'	'A'
'D'	'B'
'B'	'B'
'B'	'A'
'B'	'B'
'A'	'A'
'B'	'B'
'B'	'D'
'C'	'C'
'D'	'A'
'A'	'B'
'C'	'A'
'B'	'B'
'C'	'D'
'B'	'C'
'A'	'D'
'B'	'D'
'A'	'B'
'B'	'B'
'B'	'B'
'B'	'B'
'B'	'B'
'C'	'A'
'D'	'A'
'A'	'B'
'C'	'A'
'B'	'B'
'B'	'A'
'C'	'D'
'A'	'C'
'D'	'A'
'B'	'C'
'A'	'C'
'B'	'D'
'A'	'D'
'D'	'A'
'A'	'B'
'D'	'C'
'B'	'A'
'D'	'A'
'A'	'C'
'B'	'A'
'D'	'A'
'D'	'A'
'B'	'A'
'D'	'A'
'C'	'C'
'B'	'A'
'A'	'B'
'A'	'D'
'B'	'A'
'B'	'B'
'B'	'D'
'B'	'A'
'D'	'A'
'B'	'A'
'B'	'C'
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'B'	'C'
'C'	'C'
'A'	'D'
'A'	'D'
'A'	'C'
'B'	'B'
'C'	'C'
'D'	'A'
'B'	'D'
'B'	'A'
'B'	'B'
'A'	'A'
'D'	'A'
'B'	'A'
'D'	'A'
'B'	'C'
'C'	'B'
'B'	'D'
'A'	'A'
'B'	'B'
'B'	'B'
'A'	'C'
'A'	'B'
'D'	'B'
'D'	'C'
'D'	'A'
'A'	'B'
'C'	'A'
'A'	'D'
'D'	B'
'D'	'A'
'C'	'A'
'C'	'A'
'B'	'A'
'A'	'C'
'C'	'D'
'D'	'A'
'C'	'A'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=99763&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=99763&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=99763&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 0 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
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')