Statistics and Data Analysis

Recommended Prerequisites

Linear algebra and basic Statistical elements.

Teaching Methods

A set of slides containing the fundamental topics and a set of solved exercises are presented during all classes. Students have access to these slides and to an additional set of exercises to solve outside the classroom, although some of these are solved during classes. At the end of the course students make a final exam to test their knowledge.

Learning Outcomes

The course of Statistics and data analysis tries to provide students with basic statistical tools that allows them to:

(1) recognize where statistics can be used in the field of management and Marketing;

(2) make statistical analysis;

(3) be able to understand, analyze and criticize any statistical report;

(4) make use of statistical software.

Work Placement(s)

No

Syllabus

1. Introduction: Statistics, data and statistical thinking
2. Basic concepts: Methods for describing data sets; random variables and probability distributions.
3. Inference based on a single sample: estimation with confidence intervals and tests of hypothesis.
4. Inference based on two samples: estimation with confidence intervals and tests of hypothesis.
5. Analysis of Variance.
6. Simple linear regression.
7. Multiple regression.

Head Lecturer(s)

Rodrigo Caldeira Almeida Martins

Assessment Methods

Evaluation
Exam: 100.0%

Bibliography

McClave, J.; Benson, P.; Sincich, T. (2008) Estatística para Administração e Economia, 10ª Edição, Prentice-Hall.
Wooldridge, Jeffrey M. (2009) Introductory econometrics: a modern approach. 4th ed. South-Western/Cengage Learning.
Pestana, M, Gagueiro, J. (2005) Análise de dados para Ciências Sociais: A complementariedade do SPSS, 4ª Edição, Edições
Sílabo.