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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 15:32:59 +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/t1289921518shq6qgelz5xy47n.htm/, Retrieved Sun, 28 Apr 2024 09:53:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=95928, Retrieved Sun, 28 Apr 2024 09:53:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

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 - Conn...] [2010-11-11 18:31:44] [74be16979710d4c4e7c6647856088456]
F   P       [Chi-Squared and McNemar Tests] [Chi-Squared and M...] [2010-11-16 15:32:59] [4bfaadb29d89ff24ebcdd4f425066435] [Current]
Feedback Forum
2010-11-20 10:15:47 [7d66e2e510b144c68ca0882fd178e17c] [reply] 
Waarschijnlijk heb je hier ook niet gekeken naar de p-value zoals voorheen. De p-waarde is 0,43. Dit wijst op een toeval en dat er geen verband bestaat tussen depression en connected. Dus niet kijken naar de Chi Square Statistic waarde!
2010-11-23 08:47:10 [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.(0,43) 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, daar zien we dat de blokken allemaal naar beneden wijzen. Dit zegt dat de reële frequentie lager is dan de verwachte frequentie (stippellijn). Vervolgens kijken we naar de andere diagonaal waar we zien dat de blokken allemaal boven de stippellijn liggen wat er dus op wijst dat de reële frequentie hoger ligt dan de verwachte frequentie. Deze twee diagonalen spreken elkaar tegen waardoor we kunnen stellen dat er een verband bestaat. Omdat de hoofddiagonaal negatief is, spreken we van een negatief 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/t12900856873pn9g2meg8fz24d.htm/

Post a new message

Dataset

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

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=95928&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=95928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95928&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
Connected x Depression
HILO
HI5740
LO4322

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Depression \tabularnewline
  & HI & LO \tabularnewline
HI & 57 & 40 \tabularnewline
LO & 43 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95928&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]57[/C][C]40[/C][/ROW]
[C]LO[/C][C]43[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95928&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 Depression
HILO
HI5740
LO4322






Tabulation of Expected Results
Connected x Depression
HILO
HI59.8837.12
LO40.1224.88

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Depression \tabularnewline
  & HI & LO \tabularnewline
HI & 59.88 & 37.12 \tabularnewline
LO & 40.12 & 24.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95928&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]59.88[/C][C]37.12[/C][/ROW]
[C]LO[/C][C]40.12[/C][C]24.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95928&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95928&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 Depression
HILO
HI59.8837.12
LO40.1224.88






Statistical Results
Pearson's Chi-squared test with Yates' continuity correction
Chi Square Statistic0.61
Degrees of Freedom1
P value0.43

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test with Yates' continuity correction \tabularnewline
Chi Square Statistic & 0.61 \tabularnewline
Degrees of Freedom & 1 \tabularnewline
P value & 0.43 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95928&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]0.61[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]1[/C][/ROW]
[ROW][C]P value[/C][C]0.43[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95928&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95928&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 Statistic0.61
Degrees of Freedom1
P value0.43


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')