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42062 - Linear Models

Academic Year 2019/2020

                
                        Docente:
                        Angela Montanari
                    
                        Credits:
                        6
                    
                        SSD:
                        SECS-S/01
                    
                        Language:
                        Italian
                    
                        Teaching Mode:
                        Traditional lectures
                        
                            Campus:
                            Bologna
                        
                            Corso:
                            First cycle degree programme (L) in
                            Statistical Sciences (cod. 8873)

                            Teaching resources on Virtuale

Learning outcomes

By the end of the course the student should know the basic theory of normal linear models and should be able to apply them to the analysis of real phenomena.

In particular the student should be able:

- to define a statistical model

- to formulate the normal linear model, estimate its parameters and test their significance

- to use variable selection procedures

- to check the validity of the assumptions the model relies upon

- to perform an anlysis of variance and interpret the results

Course contents

Multiple Linear Regression: Definition, Estimation and Hypothesis Testing. Selection of Predictor Variables in the Multiple Linear Regression Model. Normal Linear Models: Analysis of Variance.

Readings/Bibliography

Lecture notes downloadable from IOL

Teaching methods

Lectures and labs using the software R

Assessment methods

Computer and oral examination

Office hours

See the website of Angela Montanari