Experimental Design and Data Analysis for Biologists

Biologists commonly record more than one variable from each sampling or experimental unit. For example, a physiologist may record blood pressure and body weight from experimental animals, or an ecologist may record the abundance of a particular species of shrub and soil pH from a series of plots during vegetation sampling. Such data are termed bivariate when we have two random variables recorded from each unit or multivariate when we have more than two random variables recorded from each unit. There are a number of relevant questions that might prompt us to collect such data, based on the nature of the biological and statistical relationship between the variables. The next two chapters consider statistical procedures for describing the relationship(s) between two or more continuous variables, and using that relationship for prediction. Techniques for detecting patterns and structure in complex multivariate data sets, and simplifying such data sets for further analyses, will be covered in Chapters 15–18.

Correlation analysis

Consider a situation where we are interested in the statistical relationship between two random variables, designated Y1 and Y2, in a population. Both variables are continuous and each sampling or experimental unit (i) in the population has a value for each variable, designated yi1 and yi2.

Land crabs on Christmas Island

Christmas Island in the northeast Indian Ocean is famous for its endemic red land crabs, Gecarcoidea natalis, which undergo a spectacular mass migration back to the ocean each year to release their eggs.