Glossary

Method of Least Squares: Method of model fitting that estimates parameters by minimizing the sum of squared errors (SSE). Assuming (1) the simple linear regression model, , (2) n data values , i=1,...,n, and (3) estimates of the intercept, and of the slope, SSE is given by SSE = . The least squares estimators and are the values of and that make SSE( )a minimum.

Pearson Correlation Coefficient: a measure of the strength of the linear association between two quantitative variables.

SSE: Sum of Squared Errors. SSE is a function that gives a measure of how far the line is from the data (see the entry on Method of Least Squares for the formula). The least squares estimators of slope and intercept are those values of and that make SSE( )a minimum.