August 2016
Intermediate to advanced
228 pages
4h 44m
English
Content preview from Introduction to R for Business IntelligenceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Checking model assumptions
To use linear regression, your data must satisfy the following four core assumptions:
- Linearity
- Independence
- Normality
- Equal variance
It may be helpful to think of these assumptions by their first letters. You can remember that LINE is an important aspect of linear regression. Next, you will learn about each of the assumptions as well as tests that you can perform in R to check whether the data satisfies them.
Note
Learn more: Checking the assumptions of a statistical model is important. The power and accuracy of any model comes from its adherence to the assumptions. David Robinson (2015) has written a blog called VARIANCE EXPLAINED that describes this topic in an enjoyable way: http://varianceexplained.org/r/kmeans-free-lunch/ ...
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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.