Frequentist Methods for Statistical Inference

Authored by: David H. Kaye

Handbook of Forensic Statistics

Print publication date:  November  2020
Online publication date:  November  2020

Print ISBN: 9781138295407
eBook ISBN: 9780367527709
Adobe ISBN:

10.1201/9780367527709-2

 Download Chapter

 

Abstract

Statistics textbooks promise that methods for statistical inference can assist in “making valid generalizations from samples” (Freedman et al., 1998, p. xvi); in “draw[ing] conclusions about a population or process based on sample data” (Moore and McCabe, 1993, p. 427); or in answering the question, “[g]iven the outcomes, what can we say about the process that generated the data?” (Wasserman, 2004, p. ix). This chapter outlines the logic of “classical” or “frequentist” methods for such inference. These methods do not purport to remove all threats to the validity of inferences, but they do provide a clear way to think about and respond to statistical error—the ubiquitous variability in outcomes that results from random influences.

 Cite
Search for more...
Back to top

Use of cookies on this website

We are using cookies to provide statistics that help us give you the best experience of our site. You can find out more in our Privacy Policy. By continuing to use the site you are agreeing to our use of cookies.