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Chi Kwadraat Test - Uitvoer & Invoer

*The author of this computation has been verified*
R Software Module: /rwasp_chi_squared_tests.wasp (opens new window with default values)
Title produced by software: Chi-Squared Test, McNemar Test, and Fisher Exact Test
Date of computation: Sat, 18 Dec 2010 12:47:40 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/18/t1292676350anyzqdfrtxif4bk.htm/, Retrieved Sat, 18 Dec 2010 13:45:53 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/18/t1292676350anyzqdfrtxif4bk.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
16198,9 16896,2 16554,2 16698 19554,2 19691,6 15903,8 15930,7 18003,8 17444,6 18329,6 17699,4 16260,7 15189,8 14851,9 15672,7 18174,1 17180,8 18406,6 17664,9 18466,5 17862,9 16016,5 16162,3 17428,5 17463,6 17167,2 16772,1 19630 19106,9 17183,6 16721,3 18344,7 18161,3 19301,4 18509,9 18147,5 17802,7 16192,9 16409,9 18374,4 17967,7 20515,2 20286,6 18957,2 19537,3 16471,5 18021,9 18746,8 20194,3 19009,5 19049,6 19211,2 20244,7 20547,7 21473,3 19325,8 19673,6 20605,5 21053,2 20056,9 20159,5 16141,4 18203,6 20359,8 21289,5 19711,6 20432,3 15638,6 17180,4 14384,5 15816,8 13855,6 15071,8 14308,3 14521,1 15290,6 15668,8 14423,8 14346,9 13779,7 13881 15686,3 15465,9 14733,8 14238,2 12522,5 13557,7 16189,4 16127,6 16059,1 16793,9 16007,1 16014 15806,8 16867,9 15160 16014,6 15692,1 15878,6 18908,9 18664,9 16969,9 17962,5 16997,5 17332,7 19858,9 19542,1 17681,2 17203,6
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time74 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Tabulation of Results
Uitvoer x Invoer
13557.71388114238.214346.914521.115071.815189.815465.915668.815672.715816.815878.615930.71601416014.616127.616162.316409.91669816721.316772.116793.916867.916896.217180.417180.817203.617332.717444.617463.617664.917699.417802.717862.917962.517967.718021.918161.318203.618509.918664.919049.619106.919537.319542.119673.619691.620159.520194.320244.720286.620432.321053.221289.521473.3
12522.51000000000000000000000000000000000000000000000000000000
13779.70100000000000000000000000000000000000000000000000000000
13855.60000010000000000000000000000000000000000000000000000000
14308.30000100000000000000000000000000000000000000000000000000
14384.50000000000100000000000000000000000000000000000000000000
14423.80001000000000000000000000000000000000000000000000000000
14733.80010000000000000000000000000000000000000000000000000000
14851.90000000001000000000000000000000000000000000000000000000
151600000000000000010000000000000000000000000000000000000000
15290.60000000010000000000000000000000000000000000000000000000
15638.60000000000000000000000001000000000000000000000000000000
15686.30000000100000000000000000000000000000000000000000000000
15692.10000000000010000000000000000000000000000000000000000000
15806.80000000000000000000000100000000000000000000000000000000
15903.80000000000001000000000000000000000000000000000000000000
16007.10000000000000100000000000000000000000000000000000000000
16016.50000000000000000100000000000000000000000000000000000000
16059.10000000000000000000001000000000000000000000000000000000
16141.40000000000000000000000000000000000000010000000000000000
16189.40000000000000001000000000000000000000000000000000000000
16192.90000000000000000010000000000000000000000000000000000000
16198.90000000000000000000000010000000000000000000000000000000
16260.70000001000000000000000000000000000000000000000000000000
16471.50000000000000000000000000000000000001000000000000000000
16554.20000000000000000001000000000000000000000000000000000000
16969.90000000000000000000000000000000000100000000000000000000
16997.50000000000000000000000000001000000000000000000000000000
17167.20000000000000000000010000000000000000000000000000000000
17183.60000000000000000000100000000000000000000000000000000000
17428.50000000000000000000000000000010000000000000000000000000
17681.20000000000000000000000000010000000000000000000000000000
18003.80000000000000000000000000000100000000000000000000000000
18147.50000000000000000000000000000000010000000000000000000000
18174.10000000000000000000000000100000000000000000000000000000
18329.60000000000000000000000000000000100000000000000000000000
18344.70000000000000000000000000000000000000100000000000000000
18374.40000000000000000000000000000000000010000000000000000000
18406.60000000000000000000000000000001000000000000000000000000
18466.50000000000000000000000000000000001000000000000000000000
18746.80000000000000000000000000000000000000000000000001000000
18908.90000000000000000000000000000000000000000100000000000000
18957.20000000000000000000000000000000000000000000100000000000
19009.50000000000000000000000000000000000000000010000000000000
19211.20000000000000000000000000000000000000000000000000100000
19301.40000000000000000000000000000000000000001000000000000000
19325.80000000000000000000000000000000000000000000001000000000
19554.20000000000000000000000000000000000000000000000100000000
196300000000000000000000000000000000000000000001000000000000
19711.60000000000000000000000000000000000000000000000000001000
19858.90000000000000000000000000000000000000000000010000000000
20056.90000000000000000000000000000000000000000000000010000000
20359.80000000000000000000000000000000000000000000000000000010
20515.20000000000000000000000000000000000000000000000000010000
20547.70000000000000000000000000000000000000000000000000000001
20605.50000000000000000000000000000000000000000000000000000100


Tabulation of Expected Results
Uitvoer x Invoer
13557.71388114238.214346.914521.115071.815189.815465.915668.815672.715816.815878.615930.71601416014.616127.616162.316409.91669816721.316772.116793.916867.916896.217180.417180.817203.617332.717444.617463.617664.917699.417802.717862.917962.517967.718021.918161.318203.618509.918664.919049.619106.919537.319542.119673.619691.620159.520194.320244.720286.620432.321053.221289.521473.3
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20359.80.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.02
20515.20.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.02
20547.70.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.02
20605.50.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.020.02


Statistical Results
Pearson's Chi-squared test
Chi Square Statistic2970
Degrees of Freedom2916
P value0.24
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292676350anyzqdfrtxif4bk/1d7rg1292676384.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/18/t1292676350anyzqdfrtxif4bk/1d7rg1292676384.ps (open in new window)


 
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')
 





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