This document discusses linear regression analysis and its use for forecasting. Linear regression finds the linear relationship between two correlated variables, where one variable can be used to predict the other. It fits a straight line to the data using the least squares method to minimize the vertical differences between the observed and predicted values. The slope of the linear regression line shows the change in the dependent variable for each unit change in the independent variable. As an example, linear regression is performed on a dataset to forecast values for periods 13 through 16. The errors are also calculated to evaluate the model fit.