Degree | Type | Year | Semester |
---|---|---|---|
4311312 Management, Organization and Business Economics | OB | 0 | 1 |
No specific preconditions although some general knowledge in statistics are more than welcome.
The module introduces multivariate methods for the quantitative analysis of large databases. It also includes methods for creating and improving measurement scales and for analysis of experimental and non-experimental data. The data used will be related to economic and business issues, with an special emphasis on introducing gender aspects in the analyses. The use of statistical packages is emphasized through exercises and applied works. The module also contains econometric methods including response models, discreet censored regression models, methods of sample selection and panel data models. Additionally, also addresses mathematical programming in the context of operational research.
The module provides vital input into decision-making in business and management. In particular, the course provides an applied introduction to data analysis. The main purpose is to provide students with the basic knowledge for developing empirical analysis and understanding the results. The approach to the subject will be essentially practical, being STATA the statistical computer package used throughout the module.
The following topics will be covered:
1. Data management, graphics and applications.
2. Descriptive statistics. Significance. Plots. Hypotheses tests.
3. Normality tests. Parametric and non-parametric tests for comparison of means.
4. Analysis of cross-classifications.
5. Measures of association.
6. Correlation.
7. Regression.
8. Logistic regression.
9. Factor analysis. Cluster analysis and property fitting.
10. Structural Equation Models.
11. Discrete choice models.
12. Censored and truncated models.
13. Panel Data.
Further details are provided in the MMOBE web page.
The module presents a practical approach, therefore sessions are scheduled in computer rooms and developed through the use of statistical packages (STATA mainly).
Generally, professors present different techniques (objectives and requirements related to the type of variables), they use the statistical packages and teach how they can be used in relation to the techniques previously commented, and finally they develop some exercises.
Other exercises and cases are assigned to the students.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Lectures, discussions and case presentations | 100 | 4 | 5, 10, 9, 16, 1, 6, 8, 14, 15 |
Type: Supervised | |||
Training and monitoring of work in progress and cases | 15 | 0.6 | 5, 10, 9, 16, 1, 6, 8, 14, 15 |
Type: Autonomous | |||
Reading related cases and practical preparation, study and preparation of schemes | 95 | 3.8 | 5, 11, 17, 13, 10, 9, 3, 2, 12, 16, 1, 4, 6, 7, 8, 14, 15 |
The system followed in the module considers 3 elements to assess the performance of the students:
1. Class participation.
2. Assignments.
3. Test.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Assignments | 40% | 30 | 1.2 | 5, 11, 17, 13, 10, 9, 3, 2, 12, 16, 1, 4, 6, 7, 8, 14, 15 |
Class participation | 5% | 0 | 0 | 5, 11, 17, 13, 10, 9, 3, 2, 12, 16, 1, 4, 6, 7, 8, 14, 15 |
Test | 55% | 10 | 0.4 | 5, 10, 9, 3, 12, 16, 1, 4, 6, 8, 14, 15 |
Afifi, A., May, S., and Clark, V.A. (2011) Practical Multivariate Analysis, 5th ed., Chapman & Hall/CRC.
Amemiya, T. (1981) Qualitative Response Models: A Survey, Journal of Economic Literature, 19: 483–536.
Cameron, A.C., and Trivedi, P.K (2009) Microeconomics using Stata, STATA Press.
Greene, W. (2003) Econometric Analysis. Fifth edition. Upper Saddler River. New Jersey, USA: Prentice – Hall.
Hair, J., Black, B., Babin, B., Anderson, R., Tatham, R. (2005) Multivariate data analysis. Sixth edition. Upper Saddler River. New Jersey, USA: Prentice – Hall.
Maddala, G. (1983) Limited Dependent and Qualitative Variables in Econometrics. Econometric Society Monographs No 3, Cambridge University Press, Cambridge, chapters 2 and 3.