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Published online by Cambridge University Press: 05 June 2012
Introduction
This chapter explains how simple linear regression analysis describes the functional relationship between a dependent and an independent variable. The different uses of correlation and regression were contrasted in Chapter 14. Correlation examines if two variables are related. Regression describes the functional relationship between a dependent and an independent variable.
Linear regression
Linear regression analysis is often used by life scientists. For example, the equation for the regression of one variable on another may suggest hypotheses about why the two variables are functionally related. More practically, regression can be used in situations where the dependent variable is difficult, expensive or impossible to measure, but its values can be predicted from another easily measured variable to which it is functionally related. Here is an example.
There is considerable variation in the height of adult humans. Consequently, parents who have a child that is relatively short for its age often become concerned that it will be relatively short when it becomes an adult. It is easy to make a person grow taller by administering human growth hormone, but this treatment becomes less and less effective after the age of ten and ineffective after about the age of 17. It also has to be used with caution because only small amounts of hormone can cause a considerable increase in growth.
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