Biostatistics For Dummies

Chapter 12

Comparing Average Values between Groups

In This Chapter

Determining which tests should be used in different situations

Preparing your data, running tests, and interpreting the output

Estimating the sample size you need to compare average values

Comparing average values between groups of numbers is part of the analysis of almost every biological experiment, and over the years statisticians have developed dozens of tests for this purpose. These tests include several different flavors of the Student t test, analyses of variance (ANOVA) and covariance (ANCOVA), and a dizzying collection of tests with such exotic-sounding names as Welch, Wilcoxon, Mann-Whitney, Kruskal-Wallis, Friedman, Tukey-Kramer, Dunnett, and Newman-Keuls, to name just a few. The number of possibilities is enough to make your head spin, and it leaves many researchers with the uneasy feeling that they may be using an inappropriate statistical test on their data.

In this chapter, I guide you through the menagerie of statistical tests for comparing groups of numbers, explaining why so many tests are out there, which ones are right for which situations, how to run them on a computer, and how to interpret ...