Introduction

Statisticians and life scientists who teach statistics are often visited in their offices by a researcher or student they may have never met before, who is clutching a dauntingly thick pile of paper and perhaps a couple of CDs with labels like ‘Experiment 1’ or ‘Trial 2’. The visitor sits down, drops everything heavily on the desk, and says, ‘Here are my results. What stats do I need?’

This is not a good thing to do. First, the person whose advice you are seeking may not have the time to work out exactly how you have done the experiment, so they may give you bad advice. Second, the answer can be a very nasty surprise like, ‘There are problems with your experimental design’.

The decision about the appropriate statistical analysis needs to be made by considering the hypothesis being tested, the experimental design, and the type of data. It can save a lot of time, trouble, and disappointment if you think about possible ways of analysing the data at the time the experiment is designed, rather than only after the data have been collected.

The following tables are a guide to choosing an appropriate test. You need to start at Table 19.1, which initially gives three columns that are mutually exclusive choices. Once you have decided among these, work downwards within the column you have chosen. There may be more choices and here you also need to select the appropriate column and continue downwards.