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Course 2022-2023 a.y.

20358 - ECONOMETRICS - PREPARATORY COURSE

Department of Economics

Course taught in English

Insegnamento offerto in modalita' e-learning


DES-ESS (I/II sem. - P) - EMIT (I/II sem. - P) - GIO (I/II sem. - P) - PPA (I/II sem. - P)
Course Director:
GIOVANNI BRUNO

Module: E-learning class-group
Instructors:
Class 1: GIOVANNI BRUNO


Class-group lessons delivered  on campus

Mission & Content Summary
MISSION

The course intends to provide students with an introduction to methods of linear regression in econometrics.

CONTENT SUMMARY

Matrix algebra useful for linear regression:

-matrix operations;

-determinants;

-linear independence;

-rank;

-inverse matrix;

-vector spaces and projection matrices;

-quadratic forms;

-calculus.  

Linear regression:  

-parameter identification

-parameter estimation;

-hypothesis testing;

-specifications tests;

-linear regression using Stata

 


Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...

      

 

APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...

apply the main procedures of linear regression in econometrics


Teaching methods
  • Face-to-face lectures
DETAILS

      

 


Assessment methods
  Continuous assessment Partial exams General exam
  • Active class participation (virtual, attendance)
  • x    
    ATTENDING AND NOT ATTENDING STUDENTS

         

     


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    Lecture notes, slides and Stata material will be uploaded in BBoard at the beginning of the course. 

    Last change 31/05/2022 10:46

    Go to modules: E-learning class-group

    DSBA (I/II sem. - P)
    Course Director:
    GIOVANNI BRUNO

    Classes: 1 (I/II sem.)
    Instructors:
    Class 1: GIOVANNI BRUNO


    Class-group lessons delivered  on campus

    Mission & Content Summary
    MISSION

    The course intends to provide students with an introduction to methods of linear regression in econometrics.

    CONTENT SUMMARY

    Matrix algebra useful for linear regression:

    -matrix operations;

    -determinants;

    -linear independence;

    -rank;

    -inverse matrix;

    -vector spaces and projection matrices;

    -quadratic forms;

    -calculus.  

    Linear regression:  

    -parameter identification

    -parameter estimation;

    -hypothesis testing;

    -specifications tests;

    -linear regression using Stata


    Intended Learning Outcomes (ILO)
    KNOWLEDGE AND UNDERSTANDING
    At the end of the course student will be able to...

        

     

    APPLYING KNOWLEDGE AND UNDERSTANDING
    At the end of the course student will be able to...

    apply the main procedures of linear regression in econometrics


    Teaching methods
    • Face-to-face lectures
    DETAILS

        

     


    Assessment methods
      Continuous assessment Partial exams General exam
  • Active class participation (virtual, attendance)
  • x    
    ATTENDING AND NOT ATTENDING STUDENTS

       

     


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    Lecture notes, slides and Stata material will be uploaded in BBoard at the beginning of the course. 

    Last change 10/06/2022 14:38