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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 Test, McNemar Test, and Fisher Exact Test
Date of computationSun, 09 Dec 2018 17:45:17 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Dec/09/t1544373942tjohaj6scpkloqv.htm/, Retrieved Sun, 28 Apr 2024 13:52:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315817, Retrieved Sun, 28 Apr 2024 13:52:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [chi sq: csurfc] [2018-12-09 16:45:17] [ed325faff554f097403cb8f6ee07a063] [Current]
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Dataseries X:
'F' 10
'M' 8
'M' 8
'M' 9
'F' 5
'M' 10
'M' 8
'M' 9
'F' 8
'F' 7
'F' 10
'F' 10
'M' 9
'F' 4
'M' 4
'M' 8
'M' 9
'M' 10
'F' 8
'F' 5
'M' 10
'F' 8
'M' 7
'M' 8
'M' 8
'F' 9
'F' 8
'M' 6
'M' 8
'F' 8
'M' 5
'M' 9
'F' 8
'F' 8
'F' 8
'F' 6
'F' 6
'M' 9
'M' 8
'M' 9
'M' 10
'F' 8
'F' 8
'F' 7
'M' 7
'M' 10
'M' 8
'M' 7
'M' 10
'M' 7
'F' 7
'F' 9
'F' 9
'F' 8
'F' 6
'F' 8
'M' 9
'F' 2
'F' 6
'M' 8
'M' 8
'F' 7
'F' 8
'F' 6
'F' 10
'F' 10
'F' 10
'F' 8
'M' 8
'M' 7
'M' 10
'F' 5
'M' 3
'M' 2
'M' 3
'M' 4
'F' 2
'F' 6
'F' 8
'F' 8
'F' 5
'M' 10
'M' 9
'M' 8
'M' 9
'M' 8
'F' 5
'M' 7
'M' 9
'F' 8
'M' 4
'M' 7
'M' 8
'F' 7
'M' 7
'F' 9
'M' 6
'F' 7
'F' 4
'M' 6
'F' 10
'M' 9
'M' 10
'F' 8
'F' 4
'M' 8
'F' 5
'M' 8
'M' 9
'F' 8
'M' 4
'F' 8
'M' 10
'F' 6
'F' 7
'M' 10
'M' 9
'M' 8
'F' 3
'F' 8
'F' 7
'F' 7
'F' 8
'M' 8
'F' 7
'M' 7
'F' 9
'M' 9
'F' 9
'M' 4
'F' 6
'M' 6
'F' 6
'F' 8
'F' 3
'F' 8
'M' 8
'M' 6
'F' 10
'F' 2
'M' 9
'M' 6
'F' 6
'F' 5
'F' 4
'F' 7
'M' 5
'M' 8
'F' 6
'M' 9
'F' 6
'M' 4
'F' 7
'M' 2
'M' 8
'M' 9
'F' 6
'M' 5
'M' 7
'M' 8
'F' 4
'M' 9
'F' 9
'M' 9
'F' 7
'M' 5
'F' 7
'M' 9
'M' 8
'M' 6
'M' 9
'M' 8
'M' 7
'F' 7
'F' 7
'F' 8
'M' 10
'F' 6
'F' 6




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315817&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315817&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315817&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center







Tabulation of Results
genderC x Intention_to_Use
1023456789
F832571516257
M1222647112522

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
genderC  x  Intention_to_Use \tabularnewline
  & 10 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 \tabularnewline
F & 8 & 3 & 2 & 5 & 7 & 15 & 16 & 25 & 7 \tabularnewline
M & 12 & 2 & 2 & 6 & 4 & 7 & 11 & 25 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315817&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]genderC  x  Intention_to_Use[/C][/ROW]
[ROW][C] [/C][C]10[/C][C]2[/C][C]3[/C][C]4[/C][C]5[/C][C]6[/C][C]7[/C][C]8[/C][C]9[/C][/ROW]
[C]F[/C][C]8[/C][C]3[/C][C]2[/C][C]5[/C][C]7[/C][C]15[/C][C]16[/C][C]25[/C][C]7[/C][/ROW]
[C]M[/C][C]12[/C][C]2[/C][C]2[/C][C]6[/C][C]4[/C][C]7[/C][C]11[/C][C]25[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315817&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315817&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
genderC x Intention_to_Use
1023456789
F832571516257
M1222647112522







Tabulation of Expected Results
genderC x Intention_to_Use
1023456789
F9.832.461.975.415.4110.8213.2724.5814.26
M10.172.542.035.595.5911.1813.7325.4214.74

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
genderC  x  Intention_to_Use \tabularnewline
  & 10 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 \tabularnewline
F & 9.83 & 2.46 & 1.97 & 5.41 & 5.41 & 10.82 & 13.27 & 24.58 & 14.26 \tabularnewline
M & 10.17 & 2.54 & 2.03 & 5.59 & 5.59 & 11.18 & 13.73 & 25.42 & 14.74 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315817&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]genderC  x  Intention_to_Use[/C][/ROW]
[ROW][C] [/C][C]10[/C][C]2[/C][C]3[/C][C]4[/C][C]5[/C][C]6[/C][C]7[/C][C]8[/C][C]9[/C][/ROW]
[C]F[/C][C]9.83[/C][C]2.46[/C][C]1.97[/C][C]5.41[/C][C]5.41[/C][C]10.82[/C][C]13.27[/C][C]24.58[/C][C]14.26[/C][/ROW]
[C]M[/C][C]10.17[/C][C]2.54[/C][C]2.03[/C][C]5.59[/C][C]5.59[/C][C]11.18[/C][C]13.73[/C][C]25.42[/C][C]14.74[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315817&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315817&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
genderC x Intention_to_Use
1023456789
F9.832.461.975.415.4110.8213.2724.5814.26
M10.172.542.035.595.5911.1813.7325.4214.74







Statistical Results
Pearson's Chi-squared test
Pearson Chi Square Statistic13.46
Degrees of Freedom8
P value0.1

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Pearson Chi Square Statistic & 13.46 \tabularnewline
Degrees of Freedom & 8 \tabularnewline
P value & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315817&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test[/C][/ROW]
[ROW][C]Pearson Chi Square Statistic[/C][C]13.46[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]8[/C][/ROW]
[ROW][C]P value[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315817&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315817&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
Pearson Chi Square Statistic13.46
Degrees of Freedom8
P value0.1



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=='Fisher Exact Test') {
(cst <- fisher.test(table1))
}
if ((par3 != 'McNemar Chi-Squared') & (par3 != 'Fisher Exact Test')) {
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)
if (par3=='Pearson Chi-Squared') a<-table.element(a, 'Pearson Chi Square Statistic', 1, TRUE)
if (par3=='Exact Pearson Chi-Squared by Simulation') a<-table.element(a, 'Exact Pearson Chi Square Statistic', 1, TRUE)
if (par3=='McNemar Chi-Squared') a<-table.element(a, 'McNemar Chi Square Statistic', 1, TRUE)
if (par3=='Fisher Exact Test') a<-table.element(a, 'Odds Ratio', 1, TRUE)
if (par3=='Fisher Exact Test') {
if ((ncol(table1) == 2) & (nrow(table1) == 2)) {
a<-table.element(a, round(cst$estimate, digits=2), 1,FALSE)
} else {
a<-table.element(a, '--', 1,FALSE)
}
} else {
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
}
a<-table.row.end(a)
if(!simulate.p.value){
if(par3!='Fisher Exact Test') {
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')