March 2018
Beginner to intermediate
570 pages
13h 42m
English
Content preview from Data Analysis with R, Second Edition - Second Edition
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Busting bootstrap myths
There are two very prevalent myths regarding the bootstrap that we will briefly address in this section.
The first is that the bootstrap is a panacea for small sample sizes. I think at least part of this myth is due to the name the bootstrap, which conjures of images of some rugged person pulling themselves up by the bootstraps and making something from nothing. Unfortunately, the bootstrap does not make something from nothing, nor does it even make more out of less. The important thing to remember is that the accuracy of your bootstrap distribution is completely dependent on the representativeness of your original sample. Refer back to Figure 8.1. Notice that, although the bootstrap distribution and the sampling distribution ...
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.