Overall objectives:

1 - Applying data analysis to real situations of the business domain.

Syllabus:

1 - Simple and multiple linear regression
2 - Logistic regression
3 - Principal components analysis
4 - Cluster analysis: hierarchical and K-means clustering

Literature/Sources:

Draper N. R., Smith H. , 1998 , Applied Regression Analysis , Wiley
Mendenhall W., Sincich T. , 2003 , A Second Course in Statistics: Regression Analysis , Prentice & Hall
Wackerly, D. D., W. Mendenhall, W., Scheaffer, R. L. , 2002 , Mathematical Statistics with Applications , Duxbury
Glantz S.A., Slinker B.K. , 2001 , Primer of Applied Regression and Analysis of Variance , McGraw-Hill
Marôco J. , 2014 , Análise Estatística com o SPSS Statistics , Report Number
Pallant J. , 2013 , SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS , McGraw-Hill
Pestana M. H., Gageiro J. N. , 2014 , Análise de Dados para as Ciências Sociais - A Complementaridade do SPSS , Edições Sílabo
Everitt B. S., Landau S., Leese M. , 2001 , Cluster Analysis , Arnold

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
Theoretical lectures and theoretical-practical classes with applied exercises, which the students are to solve using software and some input from the lecturer. Periodic evaluation based on two individual written tests (50% of the final grade each), with minimum grade of 9.5. Students who fail to reach the mininum grade in any of the tests can do a final exam to recover the grade of those tests.