Get Free Shipping on orders over $89
Evidence-Based Statistics : An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice - Peter M. B. Cahusac

Evidence-Based Statistics

An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice

By: Peter M. B. Cahusac

eText | 3 September 2020 | Edition Number 1

At a Glance

eText


$167.19

or 4 interest-free payments of $41.80 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches. The evidential approach is conceptually easier to grasp, and the calculations more straightforward to perform. This book explains how to express data in terms of the strength of statistical evidence for competing hypotheses.  

The evidential approach is currently underused, despite its mathematical precision and statistical validity. Evidence-Based Statistics is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book. 

While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician’s “bag of tricks.” In this book: 

  • It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion 
  • Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that’s ‘too good to be true’, multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps) 
  • Equations are given for all analyses, and R statistical code provided for many of the analyses 
  • Sample size calculations for evidential probabilities of misleading and weak evidence are explained 
  • Useful techniques, like Matthews’s critical prior interval, Goodman’s Bayes factor, and Armitage’s stopping rule are described 

Recommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields, Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis. 

 

on
Desktop
Tablet
Mobile

More in Probability & Statistics

All of Regression - Isabella Verdinelli

eTEXT

$104.95

Bayesian Workflow - Andrew Gelman

eTEXT

$116.60