Statistical Methods

Recommended Prerequisites

  Descriptive Statistics and Linear Algebra  

Teaching Methods

  The curricular unit requires the teaching of theoretical and practical lectures. The theoretical teaching material is accompanied by resolution of practical exercises for a better student-lecturer interaction and better understanding of the presented topics. Empirical applications are made with the use of GRETL and SPSS statistical softwares.  

Learning Outcomes

The objective of this course is to provide statistical instruments so that postgraduate students are able to specify, estimate, and analyze existing relationships with the use of real data.

Postgraduate students should be able to collect, transform and analyze statistical data to identify relationships between variables, choose the most appropriate estimation method to each problem, and make the appropriate interpretation of the results. 

Work Placement(s)

No

Syllabus

Simple and multivariate stochastic models

Estimation methods of the multivariate models

Statistical Inferences and hypothesis testing

Violation of the classical assumptions: Multicolinearity, Heteroskedasticity and Serial Correlation

Correction methods through alternative estimation methods

Dynamic models with time series data

Panel Models and estimation methods

Probabilistic Models 

Head Lecturer(s)

António Alberto Ferreira Santos

Assessment Methods

Assessment
Periodic or by final exam as given in the course information: 100.0%

Bibliography

GUJARATI, Damodar N. - Basic econometrics. 4th ed. Boston : McGraw-Hill, 2003. [BP 519.8 GUJ]

GUJARATI, Damodar N. - Econometrics by example. New York : Palgrave Macmillan, 2011. [BP 519.8 GUJ]

WOOLDRIDGE, Jeffrey M. — Introductory econometrics : a modern approach. 4th ed. [South Melbourne?] : South-Western/Cengage Learning, 2009. [BP 519.8 WOO]

MARKETING research with SPSS. Wim Janssens [et al.]. Harlow : Prentice Hall/Financial Times, 2008. [BP 658.8 MAR]