### Chapter 2. Correlation: Correlation

### Introduction to Correlation

Correlation**Correlation **is a statistical measure used to describe the *relationship* between two variables.

If two variables are related to one another, this means there is a *pattern* in how these two variables vary.

Determining the relationship between two variables requires two scores for each individual, one for each variable. Such a pair of scores is generally referred to as a **case**.

Applications of Correlation

Knowing the relationship between variables is particularly useful because it allows us to make *predictions*. Specifically, if we know how two variables are related, then we can use the value for one variable to make a prediction about the value for the other variable.

Knowledge of the relationship between variables is what allows a company such as Netflix to determine which shows to recommend you on the basis of your previously watched shows.

There exists a fairly strong relationship between an adult's height and weight:

*Taller*than average people also tend to*weigh more*than average*Shorter*than average people also tend to*weigh less*than average

Because of this relationship, we can use our knowledge of a person's height to make a prediction about their weight, and vice versa. For example:

- If we know that a person is taller than average, we can reasonably predict that they will also weigh more than average.
- If we know that a person weighs less than average, we can reasonably predict that they will also be shorter than average.

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