At some point in your career as a data analyst you may be asked to describe the association between variables or to predict one variable from another. Statistical techniques called correlation and linear regression allow us to do this.

The purpose of Pearson's Correlation Coefficient is to indicate a linear relationship between two measurement variables. This means that if you have two sets of scores, you want to know: Does one score predict another?

For example:

• Do your combined SAT scores predict your college GPA? Or why bother to take the SATs?
• Does stress predict how well you will do on an exam or other cognitive task?
  Might be good to know for people who have stressful jobs. Let's yell at our computer programmers more - then we'll get some good bugfree code.
• Does a baby's birth weight predict how many colds it will have in infancy? Doctors and parents might want to know this.

In all these cases, you want to know if one score is high, is the other also high? If one is low, is the other also low?