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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 15:45:15 +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/t1289922421o8zje5vkvwheaz8.htm/, Retrieved Fri, 03 May 2024 22:29:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=95963, Retrieved Fri, 03 May 2024 22:29:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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]
- RM D  [Chi-Squared and McNemar Tests] [Workshop 6 - Sepe...] [2010-11-11 18:34:14] [74be16979710d4c4e7c6647856088456]
F   P       [Chi-Squared and McNemar Tests] [Chi-Squared and M...] [2010-11-16 15:45:15] [4bfaadb29d89ff24ebcdd4f425066435] [Current]
Feedback Forum
2010-11-20 10:18:56 [7d66e2e510b144c68ca0882fd178e17c] [reply] 
Ook hier heb je gekeken naar de Chi Square Statistic. Je moet kijken naar de p-waarde! Bij Statistical Results zien we dat de p-waarde 0,02 is. Dit wijst op geen toeval en dat er een verband bestaat tussen happiness en depression.

Vervolgens kijken we naar de grafische output. Hier zien we dat de 4 balken niet gekleurd zijn, dit wijst op geen significante verschillen onderling en dat er dus geen verband is. Als we het totale beeld bekijken, is er wel een significant verschil. Vervolgens zien we dat er een positief verband is tussen happiness en separated. Hoe zie je dit? De twee diagonalen spreken elkaar tegen en daarom kijken we naar de hoofddiagonaal. Bij de balk van Hi happiness en Hi separated, ligt de werkelijke waarde boven de verwachte waarde en dus is er een positief verband.
2010-11-23 08:50:49 [Stefanie Van Esbroeck] [reply] 
Je maakte een correcte berekening maar je interpreteert ook hier de output verkeerd. Wederom moet je helemaal niet naar de waarde van de chi-kwadraat kijken. Eerst kijk je best naar de p-waarde.(0,02) Deze waarde is kleiner dan de type 2 fout van 5%. Waardoor we de nulhypothese kunnen verwerpen. 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, 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 waar we zien dat de blokken allemaal beneden 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, spreken we van een positief verband.”

Je had ook kunnen kijken naar de verfijnde oplossing. Hieronder kun je mijn voorbeeld zien:
http://www.freestatistics.org/blog/index.php?v=date/2010/Nov/18/t12900851682shsxvh7umf6fju.htm/

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'HI'	'HI'
'LO'	'HI'
'HI'	'LO'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'HI'
'LO'	'LO'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'LO'
'LO'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'LO'
'HI'	'LO'
'HI'	'HI'
'LO'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'LO'	'LO'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'LO'	'LO'
'HI'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'HI'	'HI'
'LO'	'LO'
'HI'	'LO'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'HI'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'LO'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'HI'
'HI'	'HI'
'LO'	'HI'
'LO'	'HI'
'LO'	'HI'
'HI'	'LO'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'HI'
'HI'	'LO'
'HI'	'LO'
'LO'	'LO'
'LO'	'LO'
'HI'	'HI'
'HI'	'HI'
'LO'	'LO'
'HI'	'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 time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95963&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95963&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95963&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'George Udny Yule' @ 72.249.76.132






Tabulation of Results
Seperated x Happiness
HILO
HI6525
LO3834

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Seperated  x  Happiness \tabularnewline
  & HI & LO \tabularnewline
HI & 65 & 25 \tabularnewline
LO & 38 & 34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95963&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Seperated  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]65[/C][C]25[/C][/ROW]
[C]LO[/C][C]38[/C][C]34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95963&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95963&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
Seperated x Happiness
HILO
HI6525
LO3834






Tabulation of Expected Results
Seperated x Happiness
HILO
HI57.2232.78
LO45.7826.22

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Seperated  x  Happiness \tabularnewline
  & HI & LO \tabularnewline
HI & 57.22 & 32.78 \tabularnewline
LO & 45.78 & 26.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95963&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Seperated  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]57.22[/C][C]32.78[/C][/ROW]
[C]LO[/C][C]45.78[/C][C]26.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95963&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95963&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
Seperated x Happiness
HILO
HI57.2232.78
LO45.7826.22






Statistical Results
Pearson's Chi-squared test with Yates' continuity correction
Chi Square Statistic5.72
Degrees of Freedom1
P value0.02

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test with Yates' continuity correction \tabularnewline
Chi Square Statistic & 5.72 \tabularnewline
Degrees of Freedom & 1 \tabularnewline
P value & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95963&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]5.72[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]1[/C][/ROW]
[ROW][C]P value[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95963&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95963&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 Statistic5.72
Degrees of Freedom1
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')