Site icon R-bloggers

Why trust some supposed laws of statistical sampling and…

[This article was first published on Isomorphismes, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.


Why trust some supposed laws of statistical sampling and convergence when you can just test them yourself? If you have a computer with R installed (also recommended: Rstudio) then you can stop dithering about whether these n=1000 studies cited in the newspapers actually resemble the truth enough, or not.

# make some people
# let's say 1e5 one-dimensional people characterised by one parameter
# like "wealth" or "health" or "support of some particular policy"
# if you want you can create subsets like "Irish" and "English"
# ... I'll leave that kind of fun to you
base <- rnorm(1e5, mean=45, sd=4)
inheritance <- exp( exp( exp( rpois(1e5, 1.1) )))
luck <- base * inheritance * rpois(1e5, 2.1)
extreme.luck <- rcauchy(1e5, location=45, scale=4)
people <- exp( base + inheritance + luck + extreme.luck )
# randomly sample the people
Nielsen <- sample( people[1:1e5], 100, replace=F )
# take some statistics of each and compare them
mean(Nielsen)
mean(people)
diff(  mean(Nielsen), mean(people)  )
# and so on
# compare histograms, compare medians, compare stdev's, compare kurtoses...

(Notice this is an economy with no geography, no choice, and no response.)

You could also simulate “biased sampling” by grabbing for example people[1:100] rather than sample(people[1:1e5], 100, replace=F). Or to be a little biased but also a little random you could make a indexes.to.sample.from < - floor( runif( 100, min=1, max=316) ^2 ). (Squaring will disperse the values with a bias towards the earlier. Think about that meaning of the parabola picture!)

Nice way to play around with:

To leave a comment for the author, please follow the link and comment on their blog: Isomorphismes.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.