1. Review of Basic Statistical Methods

  1. Bradley E. Huitema

Published Online: 14 OCT 2011

DOI: 10.1002/9781118067475.ch1

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition

How to Cite

Huitema, B. E. (2011) Review of Basic Statistical Methods, in The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118067475.ch1

Author Information

  1. Department of Psychology, Western Michigan University, Kalamazoo, Michigan, USA

Publication History

  1. Published Online: 14 OCT 2011
  2. Published Print: 14 OCT 2011

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780471748960

Online ISBN: 9781118067475

SEARCH

Keywords:

  • effect size;
  • elementary statistical decision theory;
  • elementary statistical inference;
  • measures of association;
  • nuisance variation;
  • software;
  • statistical methods

Summary

Statistical methods are often subsumed under the general headings “descriptive” and “inferential.” The emphasis in behavioral and medical science statistics books is frequently on the inferential rather than the descriptive aspects of statistics. This chapter begins with a review of conventional hypothesis testing (including elementary statistical decision theory) and interval estimation procedures for the simple randomized two-group experiment. Issues associated with standardized effect sizes, measures of association, generalization of results, and the control of nuisance variation are also presented. Random assignment plays an important role in both providing unconfounded estimates of treatment effects and in justifying statistical inference. Complex experimental designs are frequently used to provide higher power than is associated with simple randomized-groups designs.

Controlled Vocabulary Terms

effect size; statistical measures