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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 computationTue, 16 Nov 2010 15:25:08 +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/16/t1289921143azphmjuqkt2wpqc.htm/, Retrieved Sat, 04 May 2024 22:10:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=95920, Retrieved Sat, 04 May 2024 22:10:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ECEL 2008] [ECEL2008 hypothes...] [2008-06-14 21:17:24] [74be16979710d4c4e7c6647856088456]
F RMPD    [Chi-Squared and McNemar Tests] [Chi-Squared and M...] [2010-11-16 15:25:08] [4bfaadb29d89ff24ebcdd4f425066435] [Current]
Feedback Forum
2010-11-20 10:12:33 [7d66e2e510b144c68ca0882fd178e17c] [reply] 
Bij je analyse heb je gekeken naar de Chi Square Statistic. Met deze waarden kan je niet zien of er een verband is. Je moet hiervoor kijken naar de p-value. De p-waarde is 0,78. Dit wijst op een toeval en dat er geen verband bestaat tussen happiness en connected.
2010-11-23 08:35:56 [Stefanie Van Esbroeck] [reply] 
Je maakte een correcte berekening. Je paste de factoren 1 en 2 correct aan om zo een goed verband weer te geven. Er werd ook de juiste soort test gebruikt namelijk de Chi-kwadraat test, die gebruik maakt van de constructie van Yates. Deze test is nodig omdat je gebruik maakt van de Hi en Lo variabelen waardoor je een grove oplossing gaat weergeven.

De student vormt een verkeerde conclusie. Om deze output te interpreteren, moet je helemaal niet naar de waarde van de chi-kwadraat kijken. Eerst kijk je best naar de p-waarde.(0,78) Deze waarde is groter dan de type 2 fout van 5%. Waardoor we de nulhypothese kunnen aanvaarden. Daarna bekijken we de grafiek. De blokken hebben een grijze kleur. Dit wijst erop dat de cellen onderling geen significante verschillen vertonen. Dan bekijk je de hoofddiagonaal die loopt van linksboven naar rechtsonder. Daar zien we dat de blokken allemaal naar boven wijzen. Dit zegt dat de reële frequentie hoger is dan de verwachte frequentie (stippellijn). Vervolgens kijken we naar de andere diagonaal (van linksonder naar rechtsboven). Hier zie je dat de blokken allemaal onder de stippellijn liggen wat er dus op wijst dat de reële frequentie lager ligt dan de verwachte frequentie. Deze twee diagonalen spreken elkaar tegen waardoor we kunnen stellen dat er een verband bestaat. Omdat de hoofddiagonaal positief is ( alle blokken wijzen naar boven, is dit een positief verband.”

Je had ook kunnen kijken naar de verfijnde oplossing. Je doet dit door de data in te geven met A en B’s uit de Excel. In plaats van een gewone Chi-squared-test te gebruiken, gebruik je de “Exact Pearson Chi-squared by simulation”. Je interpreteert die op de zelfde wijze als de grove oplossing. Hieronder kan je een correcte berekening terugvinden van een verfijnde oplossing: http://www.freestatistics.org/blog/index.php?v=date/2010/Nov/18/t1290083384wud1i77335tog0r.htm/.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'HI'	'HI'
'HI'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'LO'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'HI'	'LO'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'LO'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'LO'
'HI'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'LO'	'HI'
'HI'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'LO'
'LO'	'HI'
'HI'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'LO'	'LO'
'LO'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'HI'
'LO'	'LO'
'LO'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'LO'
'LO'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'LO'
'LO'	'LO'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'LO'
'LO'	'HI'
'LO'	'HI'
'HI'	'LO'
'LO'	'LO'
'HI'	'LO'

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'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=95920&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=95920&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95920&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'George Udny Yule' @ 72.249.76.132






Tabulation of Results
Connected x Hapiness
HILO
HI6334
LO4025

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Hapiness \tabularnewline
  & HI & LO \tabularnewline
HI & 63 & 34 \tabularnewline
LO & 40 & 25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95920&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Hapiness[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]63[/C][C]34[/C][/ROW]
[C]LO[/C][C]40[/C][C]25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95920&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95920&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 Hapiness
HILO
HI6334
LO4025






Tabulation of Expected Results
Connected x Hapiness
HILO
HI61.6735.33
LO41.3323.67

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Hapiness \tabularnewline
  & HI & LO \tabularnewline
HI & 61.67 & 35.33 \tabularnewline
LO & 41.33 & 23.67 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95920&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Hapiness[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]61.67[/C][C]35.33[/C][/ROW]
[C]LO[/C][C]41.33[/C][C]23.67[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95920&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95920&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 Hapiness
HILO
HI61.6735.33
LO41.3323.67






Statistical Results
Pearson's Chi-squared test with Yates' continuity correction
Chi Square Statistic0.08
Degrees of Freedom1
P value0.78

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test with Yates' continuity correction \tabularnewline
Chi Square Statistic & 0.08 \tabularnewline
Degrees of Freedom & 1 \tabularnewline
P value & 0.78 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95920&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test with Yates' continuity correction[/C][/ROW]
[ROW][C]Chi Square Statistic[/C][C]0.08[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]1[/C][/ROW]
[ROW][C]P value[/C][C]0.78[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95920&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95920&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 Yates' continuity correction
Chi Square Statistic0.08
Degrees of Freedom1
P value0.78


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')