July 2012
Intermediate to advanced
352 pages
9h 30m
English
book
Common Errors in Statistics (and How to Avoid Them), 4th Edition
by Phillip I. Good, James W. Hardin
Content preview from Common Errors in Statistics (and How to Avoid Them), 4th Edition
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OBJECTIVES
A host of advertisements for new proprietary software claim an ability to uncover relationships previously hidden and to overcome the deficiencies of linear regression. But how can we determine whether or not such claims are true?
Good [2001; Chapter 10] reports on one such claim from the maker of PolyAnalyst™. He took the 400 records, each of 31 variables, PolyAnalyst provided in an example dataset, split the data in half at random, and obtained completely discordant results with the two halves, whether they were analyzed with PolyAnalyst, CART, or stepwise linear regression. This was yet another example of a spurious relationship that did not survive the validation process.
In this chapter, we review the various methods of validation and provide guidelines for their application.
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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.