The R Book

9

Statistical Modelling

The hardest part of any statistical work is getting started. And one of the hardest things about getting started is choosing the right kind of statistical analysis. The choice depends on the nature of your data and on the particular question you are trying to answer. The key is to understand what kind of response variable you have, and to know the nature of your explanatory variables. The response variable is the thing you are working on: it is the variable whose variation you are attempting to understand. This is the variable that goes on the y axis of the graph. The explanatory variable goes on the x axis of the graph; you are interested in the extent to which variation in the response variable is associated with variation in the explanatory variable. You also need to consider the way that the variables in your analysis measure what they purport to measure. A continuous measurement is a variable such as height or weight that can take any real numbered value. A categorical variable is a factor with two or more levels: sex is a factor with two levels (male and female), and colour might be a factor with seven levels (red, orange, yellow, green, blue, indigo, violet).

It is essential, therefore, that you can answer the following questions:

• Which of your variables is the response variable?
• Which are the explanatory variables?
• Are the explanatory variables continuous or categorical, or a mixture of both?
• What kind of response variable do you have: is it a continuous ...