June 2016
Beginner to intermediate
398 pages
8h 51m
English
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Summary
Statistical inference to evaluate the uncertainty/variability of estimations is usually challenging in classical statistics. But this is not true when resampling methods are used, data-oriented methods to make valid inference, perfectly suited for data scientists.
The bootstrap is a general tool to estimate the variance of an estimator. The estimation of the variance of a very complex statistic is as easy as estimating the variance of a simple estimator such as the arithmetic mean.
We saw that another popular resampling method – the jackknife – is by far not as trustable as the bootstrap, especially for non-smooth estimators. However, the jackknife is a useful tool to estimate the variance of the bootstrap variance estimate, for example. ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.