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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 Test, McNemar Test, and Fisher Exact Test
Date of computationThu, 15 Dec 2016 11:38:18 +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/2016/Dec/15/t1481798371ca27dxtbr9cjy3c.htm/, Retrieved Fri, 01 Nov 2024 03:39:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299837, Retrieved Fri, 01 Nov 2024 03:39:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgeslacht met TCVD1
Estimated Impact158

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ML Fitting and QQ Plot- Normal Distribution] [Normal distribution] [2016-12-15 09:27:42] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chisquared simula...] [2016-12-15 10:38:18] [9a9519454d094169f95f881e5b6f16f7] [Current]
- RMPD      [Univariate Data Series] [Plot] [2016-12-21 12:13:06] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Variance Reduction Matrix] [VRM] [2016-12-21 12:16:18] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 12:17:37] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 12:19:52] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2016-12-21 12:20:52] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 12:22:23] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Backward selectio...] [2016-12-21 12:25:13] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Arima backwards p...] [2016-12-21 12:27:09] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Forecasting] [ARIMA forecasting ] [2016-12-21 12:29:45] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Univariate Data Series] [Plot] [2016-12-21 12:32:58] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Variance Reduction Matrix] [VRm] [2016-12-21 12:34:04] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 12:35:07] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 12:36:32] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2016-12-21 12:37:50] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 12:40:01] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 13:06:54] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 13:20:15] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [a] [2017-01-22 21:09:42] [29aab2222b4b721088e78b64014cd237]
- RMPD      [Standard Deviation-Mean Plot] [sd mean plot] [2016-12-21 13:22:01] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 13:36:48] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Arima backwards] [2016-12-21 13:45:55] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Forecasting] [ARIMA forecast] [2016-12-21 13:49:45] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	4
2	5
2	4
2	4
1	4
2	5
2	5
2	4
1	4
1	5
1	5
1	4
1	4
1	4
1	4
2	5
1	4
2	3
2	4
2	5
1	4
2	5
2	4
1	4
1	3
1	4
1	4
1	4
1	4
1	3
2	4
1	5
1	4
2	4
1	5
1	4
2	3
1	2
1	5
2	4
2	5
2	4
2	4
2	4
2	3
2	4
2	4
2	3
1	3
2	5
1	5
2	5
2	2
1	3
2	2
1	4
1	5
2	4
1	4
2	5
2	5
2	4
2	5
1	4
2	4
1	5
2	3
1	2
2	5
2	4
2	4
1	4
2	3
1	5
2	4
1	5
2	3
1	2
2	5
2	4
1	1
1	4
1	5
2	4
2	5
2	4
2	5
2	4
1	5
2	5
1	4
1	4
1	4
1	4
2	4
2	4
2	4
1	5
2	5
2	4
1	4
1	4
2	2
2	4
2	4
2	4
1	4
1	4
1	4
2	4
2	4
2	4
1	3
1	5
2	4
1	5
1	4
2	5
1	3
1	4
1	3
2	4
2	4
2	4
2	4
2	5
1	4
1	4
2	4
2	2
2	4
1	4
2	3
1	2
1	4
1	4
1	3
2	4
1	5
1	4
1	3
1	3
2	4
1	3
2	4
2	2
2	5
2	4
1	4
1	3
1	4
1	5
2	4
2	2
2	4
2	5
1	4
2	4
1	5
2	4
1	5
1	3
1	4
1	4
1	3
2	4
2	4
1	3

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299837&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299837&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299837&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Tabulation of Results
geslacht x TVCD1
12345
114154319
20685022

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
geslacht  x  TVCD1 \tabularnewline
  & 1 & 2 & 3 & 4 & 5 \tabularnewline
1 & 1 & 4 & 15 & 43 & 19 \tabularnewline
2 & 0 & 6 & 8 & 50 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299837&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]geslacht  x  TVCD1[/C][/ROW]
[ROW][C] [/C][C]1[/C][C]2[/C][C]3[/C][C]4[/C][C]5[/C][/ROW]
[C]1[/C][C]1[/C][C]4[/C][C]15[/C][C]43[/C][C]19[/C][/ROW]
[C]2[/C][C]0[/C][C]6[/C][C]8[/C][C]50[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299837&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299837&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
geslacht x TVCD1
12345
114154319
20685022






Tabulation of Expected Results
geslacht x TVCD1
12345
10.494.8811.2345.3920.01
20.515.1211.7747.6120.99

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
geslacht  x  TVCD1 \tabularnewline
  & 1 & 2 & 3 & 4 & 5 \tabularnewline
1 & 0.49 & 4.88 & 11.23 & 45.39 & 20.01 \tabularnewline
2 & 0.51 & 5.12 & 11.77 & 47.61 & 20.99 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299837&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]geslacht  x  TVCD1[/C][/ROW]
[ROW][C] [/C][C]1[/C][C]2[/C][C]3[/C][C]4[/C][C]5[/C][/ROW]
[C]1[/C][C]0.49[/C][C]4.88[/C][C]11.23[/C][C]45.39[/C][C]20.01[/C][/ROW]
[C]2[/C][C]0.51[/C][C]5.12[/C][C]11.77[/C][C]47.61[/C][C]20.99[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299837&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299837&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
geslacht x TVCD1
12345
10.494.8811.2345.3920.01
20.515.1211.7747.6120.99






Statistical Results
Pearson's Chi-squared test with simulated p-value (based on 2000 replicates)
Exact Pearson Chi Square Statistic4.18
P value0.36

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test with simulated p-value
	 (based on 2000 replicates) \tabularnewline
Exact Pearson Chi Square Statistic & 4.18 \tabularnewline
P value & 0.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299837&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test with simulated p-value
	 (based on 2000 replicates)[/C][/ROW]
[ROW][C]Exact Pearson Chi Square Statistic[/C][C]4.18[/C][/ROW]
[ROW][C]P value[/C][C]0.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299837&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299837&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 with simulated p-value (based on 2000 replicates)
Exact Pearson Chi Square Statistic4.18
P value0.36


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
R code (references can be found in the software module):
par3 <- 'Pearson Chi-Squared'
par2 <- '2'
par1 <- '1'
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')