In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students that this is the best approach. In this work linear and nonlinear regressions are statistically compared in a simple heat transfer laboratory experiment.