Degree | Type | Year |
---|---|---|
4311312 Management, Organization and Business Economics | OB | 0 |
You can view this information at the end of this document.
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 course also gives an introduction to qualitative methods.
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:
Part 1
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.
Part 2
1. Basic knowledge of Social Research terminology (Ontology, Epistemology, etc.)
2. Interviews and focus groups
3. Grounded Theory for Management studies
4. Basic Training in use of a computer package to assist with qualitative data analysis (e.g. NVivo)
5. Thematic análisis
Further details are provided in the MMOBE web page.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Lectures, discussions and case presentations | 100 | 4 | 1, 6, 7, 9, 10, 11, 15, 16, 17 |
Type: Supervised | |||
Training and monitoring of work in progress and cases | 15 | 0.6 | 1, 6, 7, 9, 10, 11, 15, 16, 17 |
Type: Autonomous | |||
Reading related cases and practical preparation, study and preparation of schemes | 95 | 3.8 | 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 |
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.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Assignments | 40% | 30 | 1.2 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 |
Class participation | 5% | 0 | 0 | 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 |
Test | 55% | 10 | 0.4 | 1, 3, 5, 6, 7, 9, 10, 11, 13, 15, 16, 17 |
The system followed in the module considers 3 elements to assess the performance of the students:
1. Class participation.
2. Assignments.
3. Test.
This subject/module does not offer the option for comprehensive evaluation.
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.
GIOIA, D. A., CORLEY, K.G., HAMILTON, A.L. (2013). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational research methods, vol. 16, no 1, p. 15-31.
Greene, W. (2003) Econometric Analysis. Fifth edition. Upper Saddler River. New Jersey, USA: Prentice – Hall.
GRIX, J. (2002). Introducing students to the generic terminology of social research. Politics, vol. 22, no 3, p. 175-186.Hair, J., Black, B., Babin, B., Anderson, R., Tatham, R. (2005) Multivariate data analysis. Sixth edition. Upper Saddler River. New Jersey, USA: Prentice – Hall.
Hair, J., Black, B., Babin, B., Anderson, R., Tatham, R. (2010) 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.
STATA, NVivo
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PLABm) Practical laboratories (master) | 30 | English | second semester | morning-mixed |
(TEm) Theory (master) | 30 | English | second semester | morning-mixed |