#### LINEAR MODELS

After successfully completing this lesson, student should be able to:

1. Perform basic matrix algebra and identify matrices that are of full rank.

2. Distinguish between linear and nonlinear models.

3. Use methods of ordinary least squares and maximum likelihood to estimate the parameters of a regression model.

4. Fit simple and multiple linear regression models to given data sets.

5. Examine the adequacy of regression models.

6. Perform hypotheses testing to determine the overall significance of the regression model and that of the estimated parameters.

1. Perform basic matrix algebra and identify matrices that are of full rank.

2. Distinguish between linear and nonlinear models.

3. Use methods of ordinary least squares and maximum likelihood to estimate the parameters of a regression model.

4. Fit simple and multiple linear regression models to given data sets.

5. Examine the adequacy of regression models.

6. Perform hypotheses testing to determine the overall significance of the regression model and that of the estimated parameters.