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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, 10 Nov 2010 14:55:39 +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/10/t1289400895fhbh5fc6t1w7kvu.htm/, Retrieved Mon, 29 Apr 2024 09:39:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=93053, Retrieved Mon, 29 Apr 2024 09:39:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Chi-Squared and McNemar Tests] [Connected Separate] [2010-11-10 14:55:39] [61e5ee05de011f44efa37f086a4e2271] [Current]
-         [Chi-Squared and McNemar Tests] [Connected-Separate] [2010-11-16 15:45:15] [de4adef75375d243bafd27c3fb0ddf4c]
-         [Chi-Squared and McNemar Tests] [Worshop 6 part 1 A] [2010-11-16 19:27:32] [a90833f600c49a37df2affa5b2163a2e]
Feedback Forum
2010-11-17 20:40:49 [] [reply] 
Algemene opmerking: Als je de Chi-squared test uitvoert is er blijkbaar een bijkomende voorwaarde, namelijk de minimum cell count moet gelijk zijn aan 5. In de berekening zie je in de tabel van de berekeningen of er al dan niet lage cell-counts zijn. Indien er lage cell-counts zijn, moet je een speciale type van Chi-squared test gebruiken, namelijk deze met een gesimuleerde p-value. Dit is een simulatietechniek die ook toepasbaar is voor lage cell-counts.
2010-11-17 20:46:31 [] [reply] 
In de tabel van de berekeningen zie je lage cell counts (namelijk kleiner dan 5). Dus Chi-Squared test gebruiken met gesimuleerde p-value. Zo kom je een p-value van 1% uit. En kunnen we concluderen dat er inderdaad een duidelijk verband is tussen beiden. Als je in de grafiek kijkt naar de hoofddiagonaal, zie je ook duidelijk dat de afwijkingen naar boven wijzen, dus we kunnen spreken over een positief verband. Hoe hoger de connected leerattitude, hoe hoger de separate leerattitude.
Het is ook mogelijk om dit te berekenen bij de 2 onderverdelingen, namelijk high en low. Ook dan zie je een sterk positief verband tussen de 2 leerattitudes.

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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93053&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93053&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93053&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Tabulation of Results
Connected x Separate
ABCD
A2214117
B1313116
C810109
D19612

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Separate \tabularnewline
  & A & B & C & D \tabularnewline
A & 22 & 14 & 11 & 7 \tabularnewline
B & 13 & 13 & 11 & 6 \tabularnewline
C & 8 & 10 & 10 & 9 \tabularnewline
D & 1 & 9 & 6 & 12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93053&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Separate[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]22[/C][C]14[/C][C]11[/C][C]7[/C][/ROW]
[C]B[/C][C]13[/C][C]13[/C][C]11[/C][C]6[/C][/ROW]
[C]C[/C][C]8[/C][C]10[/C][C]10[/C][C]9[/C][/ROW]
[C]D[/C][C]1[/C][C]9[/C][C]6[/C][C]12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93053&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93053&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:

Tabulation of Results
Connected x Separate
ABCD
A2214117
B1313116
C810109
D19612






Tabulation of Expected Results
Connected x Separate
ABCD
A14.6715.3312.6711.33
B11.6812.2110.099.02
C10.0510.518.687.77
D7.67.956.575.88

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Separate \tabularnewline
  & A & B & C & D \tabularnewline
A & 14.67 & 15.33 & 12.67 & 11.33 \tabularnewline
B & 11.68 & 12.21 & 10.09 & 9.02 \tabularnewline
C & 10.05 & 10.51 & 8.68 & 7.77 \tabularnewline
D & 7.6 & 7.95 & 6.57 & 5.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93053&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Separate[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]14.67[/C][C]15.33[/C][C]12.67[/C][C]11.33[/C][/ROW]
[C]B[/C][C]11.68[/C][C]12.21[/C][C]10.09[/C][C]9.02[/C][/ROW]
[C]C[/C][C]10.05[/C][C]10.51[/C][C]8.68[/C][C]7.77[/C][/ROW]
[C]D[/C][C]7.6[/C][C]7.95[/C][C]6.57[/C][C]5.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93053&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93053&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:

Tabulation of Expected Results
Connected x Separate
ABCD
A14.6715.3312.6711.33
B11.6812.2110.099.02
C10.0510.518.687.77
D7.67.956.575.88






Statistical Results
Pearson's Chi-squared test
Chi Square Statistic20.1
Degrees of Freedom9
P value0.02

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 20.1 \tabularnewline
Degrees of Freedom & 9 \tabularnewline
P value & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93053&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]20.1[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]9[/C][/ROW]
[ROW][C]P value[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93053&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93053&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:

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic20.1
Degrees of Freedom9
P value0.02


Figures (Output of Computation)

Input Parameters & R Code

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