Hi Jan,

Glad to hear the post is useful to you! :D Here's a practical, self-contained example of bootstrapping: https://cran.r-project.org/web/packages/broom/vignettes/bootstrapping.html

And an excerpt from my own work: https://github.com/wikimedia-research/Discovery-Search-Test-PhraseRescoreBoost/blob/39a02f6a65b7893b6b13d9b65af42f9861bfa4eb/cda.R#L90--L106 because I needed to bootstrap the distribution of a K-L divergence metric (https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence)

Also, if you are using the R package "forecast" for ARIMA models, one of the options in predict.Arima (I think) is to create confidence intervals for the forecast by bootstrapping residual errors :)

Hope that helps!

- Mikhail

On Saturday, February 4, 2017, Jan Dittrich <jan.dittrich@wikimedia.de> wrote:
Hello Analytics,

I read "Hiring a data scientist" (https://blog.wikimedia.org/2017/02/02/hiring-data-scientist/) recently and it gave us a lot of useful insights into our (WMDEs) process of hiring a Data Analyst.

I stumbled upon the Bootstrap question and was reminded that I should extend my knowledge there; I read about the theory behind but I never used it in practice, so I wondered if one of you has some examples to share where you used bootstrapping in your work (Ideally in a iPython or RMarkdown notebook, which usefulness was also highlighted in the Job post :-) )

Jan

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Jan Dittrich
UX Design/ User Research

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