SAS® ’s implementation of linear regression is often used to fit a line without checking the underlying assumptions of the model or understanding the output. As a result, we can sometimes fit a line that is not appropriate for the data and get erroneous results. This paper gives a brief introduction to fitting a line with PROC REG, including assessing model assumptions and output to tell us if our results are valid. We then illustrate how one kind of data (time series data) can sometimes give us misleading results even when these model diagnostics appear to indicate that the results are correct. A simple method is proposed to avoid this.