Statistics: An Introduction Using R, 2nd Edition

1Fundamentals

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 truth is that there is no substitute for experience: the way to know what to do is to have done it properly lots of times before.

The key is to understand what kind of response variable you have got, 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 ordinate). The explanatory variable goes on the x axis of the graph (the abscissa); you are interested in the extent to which variation in the response variable is associated with variation in the explanatory variable. A continuous measurement is a variable like 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 rainbow might be a factor with seven levels (red, orange, yellow, green, blue, indigo, violet).

It is essential, therefore, that you know:

• 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 have ...