[R] Listing tables together from random samples from a generated population?
.
HI there,
I'd like to show demonstrate how the chi-squared distribution works, so I've
come up with a sample data frame of two categorical variables
y-data.frame(gender=sample(c('Male', 'Female'), size=10, replace=TRUE,
c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=10, replace=TRUE, c(0.5,
0.5)))
And I'd like to create a list of 100 different samples of those two variables
and the resulting 2X2 contingency tables
table(.y[sample(nrow(.y), 100), ])
How would I combine these 100 tables into a list? I'd like to be able to go in
and find some of the extreme values to show how the sampling distribution of
the chi-square values.
I can already get a histogram of 100 different chi-squared values that shows
the distribution nicely (see below), but I'd like to actually show the
underlying tables, for demonstration's sake.
.z-vector()
for (i in 1:100) {
.z-c(.z, chisq.test(table(.y[sample(nrow(.y), 200), ]))$statistic)
}
hist(.z, xlab='Chi-Square Value', main=Chi-Squared Values From 100 different
samples asking\nabout gender and tea/coffee drinking)
abline(v=3.84, lty=2)
Thank you in advance,
Simon Kiss
*
Simon J. Kiss, PhD
Assistant Professor, Wilfrid Laurier University
73 George Street
Brantford, Ontario, Canada
N3T 2C9
Cell: +1 905 746 7606
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Re: [R] Listing tables together from random samples from a generated population?
You could try something like this:
tables - lapply(seq(100), function(i) table(.y[sample(nrow(.y),
200), ]))
Then you could conduct the chi-squared tests
chisqs - lapply(tables, chisq.test)
and save the values
.z - sapply(chisqs, [[, statistic)
Jean
---
Simon Kiss wrote on 11/10/2011 15:48:38:
HI there,
I'd like to show demonstrate how the chi-squared distribution works, so
I've come up with a sample data frame of two categorical variables
y-data.frame(gender=sample(c('Male', 'Female'), size=10,
replace=TRUE, c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=10,
replace=TRUE, c(0.5, 0.5)))
And I'd like to create a list of 100 different samples of those two
variables and the resulting 2X2 contingency tables
table(.y[sample(nrow(.y), 100), ])
How would I combine these 100 tables into a list? I'd like to be able to
go in and find some of the extreme values to show how the sampling
distribution of the chi-square values.
I can already get a histogram of 100 different chi-squared values that
shows the distribution nicely (see below), but I'd like to actually show
the underlying tables, for demonstration's sake.
.z-vector()
for (i in 1:100) {
.z-c(.z, chisq.test(table(.y[sample(nrow(.y), 200), ]))$statistic)
}
hist(.z, xlab='Chi-Square Value', main=Chi-Squared Values From 100
different samples asking\nabout gender and tea/coffee drinking)
abline(v=3.84, lty=2)
Thank you in advance,
Simon Kiss
Simon J. Kiss, PhD
Assistant Professor, Wilfrid Laurier University 73 George Street
Brantford, Ontario, Canada
N3T 2C9
Cell: +1 905 746 7606
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Listing tables together from random samples from a generated population?
Hi:
There are two ways you could go about this: lists or arrays. It's
pretty easy to generate an array, a little more work to get the list.
I'm assuming the objective is to extract a chi-square statistic from
each table, so I'll show a couple of ways to do that, too.
library('plyr')
## Start with the data:
y-data.frame(gender=sample(c('Male', 'Female'), size=10,
replace=TRUE, c(0.5, 0.5)),
tea=sample(c('Yes', 'No'), size=10,
replace=TRUE, c(0.5, 0.5)))
## Function to produce a table:
tabfun - function(d) table(d[sample(seq_len(nrow(d)), 100), ])
x2stat - function(m) chisq.test(m)$statistic
## Array version:
tbarr - replicate(100, tabfun(y))
# X^2 statistics using apply() from base R and
# aaply() from plyr:
u1 - apply(tablist, 3, x2stat)
u2 - aaply(tablist, 3, x2stat)
## List version:
tblst - vector('list', 100)
for(i in seq_along(tblst)) tblst[[i]] - tabfun(y)
v1 - unname(do.call(c, lapply(tblst, x2stat)))
v2 - laply(tblst, x2stat)
From here, it's easy to do the histogram :)
HTH,
Dennis
On Thu, Nov 10, 2011 at 12:48 PM, Simon Kiss sjk...@gmail.com wrote:
.
HI there,
I'd like to show demonstrate how the chi-squared distribution works, so I've
come up with a sample data frame of two categorical variables
y-data.frame(gender=sample(c('Male', 'Female'), size=10, replace=TRUE,
c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=10, replace=TRUE, c(0.5,
0.5)))
And I'd like to create a list of 100 different samples of those two variables
and the resulting 2X2 contingency tables
table(.y[sample(nrow(.y), 100), ])
How would I combine these 100 tables into a list? I'd like to be able to go
in and find some of the extreme values to show how the sampling distribution
of the chi-square values.
I can already get a histogram of 100 different chi-squared values that shows
the distribution nicely (see below), but I'd like to actually show the
underlying tables, for demonstration's sake.
.z-vector()
for (i in 1:100) {
.z-c(.z, chisq.test(table(.y[sample(nrow(.y), 200), ]))$statistic)
}
hist(.z, xlab='Chi-Square Value', main=Chi-Squared Values From 100 different
samples asking\nabout gender and tea/coffee drinking)
abline(v=3.84, lty=2)
Thank you in advance,
Simon Kiss
*
Simon J. Kiss, PhD
Assistant Professor, Wilfrid Laurier University
73 George Street
Brantford, Ontario, Canada
N3T 2C9
Cell: +1 905 746 7606
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
