After approval in the course unit, the student should have the ability to:

1. Apply data pre-processing techniques that allow its subsequent treatment and analysis. Use of analysis in main components as a method to reduce the size of the data.
2. Apply methods of exploratory data analysis to recognize the main characteristics of a multivariate data set.
3. Identify and apply the concepts of reliability theory.
4. Identify and implement a linear regression model appropriate to the analytical and computational resolution of a particular problem.
5. Analyze, evaluate and interpret critically the results of the models.
6. Identify and implement clustering analysis methods. Evaluate and interpret with critical sense, the results obtained. Analyze and characterize the identified groups.

Curricular Unit Form