COMM 215 Chapter Notes - Chapter 11: Simple Linear Regression, Regression Analysis, Point Estimation
7 Apr 2017
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The measure of the strength of the linear relationship between x and y is called the covariance. This is a point predictor of the population covariance. Generally when two variables (x and y) move in the same direction (both increase or both decrease), the covariance is large and positive. It follows that generally when two variables move in the opposite directions (one increases while the other decreases), the covariance is a large negative number. When there is no particular pattern, the covariance is a small number. It is sometimes difficult to determine without a further statistic which we call the correlation coefficient. The correlation coefficient gives a value between 1 and +1. This is a point predictor of the population correlation coefficient (pronounced rho). Example: calculate the covariance and the correlation coefficient. Consider the following sample data: x is the independent variable (predictor). y is the dependent variable (predicted).
