Chapter 16
Showing Relationships between Continuous Dependent and Independent Variables
In This Chapter
Viewing relationships
Running the bivariate procedure
Running the linear regression procedure
Making predictions
The two most commonly used statistical techniques to analyze relationships between continuous variables are the Pearson correlation and linear regression.
Many people use the term correlation to refer to the idea of a relationship between variables or a pattern. This view of the term correlation is correct, but correlation also refers to a specific statistical technique. Pearson correlations are used to study the relationship between two continuous variables. For example, you may want to look at the relationship between height and weight, and you may find that as height increases, so does weight. In other words, in this example, the variables are correlated with each other because changes in one variable impact the other.
Whereas correlation just tries to determine if two variables are related, linear regression takes this one step further and tries to predict the values ...
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