In the previous modules, you learned how to estimate the parameters of interest based on the principles of (weighted) least squares or best linear unbiased estimation. Also, we learned how to describe the precision of the final results.  But just knowing the estimate of the parameters and their precision is not sufficient. All the obtained results are based on the assumption that the assumed mathematical model is correct. To see whether the results makes sense or not, we need to take one more step and check the general/overall validity of the assumed mathematical model.

Learning objectives:

By the end of this module you will be able to:

• Explain and apply the concept of overall model test to check the overall validity of the mathematical model
• Explain and hypothesize of the reasons which may cause the rejection of a mathematical model.