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Learning outcomes |
With this curricular unit it is intended that the students deepen the fundamental knowledge of statistics for analysis of real data, oriented to the Marketing area. It is also essential to develop essential data processing skills to support research.
Students should:
- Understand and apply the basic concepts of Descriptive Statistics, Sampling and Statistical Inference;
- Apply these methods to real problems and situations;
- Understand and apply other statistical techniques to support the development of research work (regression analysis, Analysis of variance of one or more factors, factorial analysis, contingency tables and Chi-square tests, Discriminant Analysis)
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Main Bibliography |
Pinto, J. Carlos Castro e Curto, J. J. Dias, "Estatística para Economia e Gestão: Instrumentos de Apoio à Tomada de Decisão", Edições Silabo, Lda., Lisboa, 1999.
Hair, Joseph F., Bill Black, Barry Babin, Rolph E. Anderson, Ronald L. Tatham (2006) Multivariate Data Analysis, 6/e, Upper Saddle River, US: Prentice Hall,
Lisboa, João V., Augusto, Mário G. e Ferreira, Pedro L. (2012), “Estatística Aplicada à Gestão”, Vida Económica, Lisboa.
Malhotra, Naresh K. e David F. Birks (2010) Marketing Research – An Applied Approach (6th ed.), Edinburgh Gate, UK: Prentice Hall,
Marôco, J. (2011). Análise Estatística com o SPSS Statistics (5th ed.), Pero Pinheiro: Edições Silabo
McClave, James T., Benson, P. George e Sincich, Terry (2001) Statistics for Business and Economics (8th Ed.), Upper Saddle Rive, US: Prentice Hall, ISBN: 0-13-027293-0
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Teaching Methodologies and Assessment Criteria |
The teaching methodology comprises two components. The first one is an expository approach, where the terms, concepts and models of statistical analysis are presented and interpreted.
The second is a practical approach where, using the SPSS software, the different statistical methods are presented, the different model estimation procedures are executed and explained and, finally, the obtained outputs are analyzed and discussed.
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