Quantitative Methods

This syllabus is only as an informative orientation for new students.
Every academic year, professors will give to the students the updated syllabus with the exact contents and evaluation system.

 
Alexandra Simon (UAB)
alexandra.simon@uab.cat

 

PURPOSE

This part of the course includes different multivariate statistical techniques (regression, logit, cluster, factor analysis, structural equation models) and their associated statistical computer packages (basically STATA) aimed at testing hypotheses and deriving conclusions about the available information.

The approach to the subject is essentially practical; the objective is to provide students with the basic knowledge for developing empirical research. Throughout the course, students are expected to carry out several assignments where the techniques explained should be applied.

 

REQUIREMENTS

Previous knowledge of basic statistics is required. More precisely, students should be familiar with the following concepts:

  • Descriptive statistics: frequencies analysis, measures of central tendency (mean,
    median, mode) and dispersion (range, quartiles, variance, standard deviation).
  • Probability: concept and probability rules.
  • Normal Distribution: compute probabilities using the standard normal table.
  • Sampling distributions: concept and applications of the Central Limit Theorem.

For a refresher on these concepts, students are recommended to review any introductory statistics book they may be familiar with. Alternatively, the following books on "statistics for business" or economics are highly recommended:

FLEMING, M.C. & NELLIS, J.G. (1996): The Essence of statistics for business.2nd ed. Harlow [etc.]: Prentice-Hall

HILDEBRAND, D. K. & OTT, L. (1991): Statistical thinking for managers. 3rd ed. Boston: PWS-Kent Pub. Co. The Duxbury series in statistics and decision sciences

JOHNSON, R. (1988): Elementary statistics. 5th ed. Boston: PWS-KENT. The Duxbury series in statistics and decision sciences.

KENKEL, J. L. (1989): Introductory statistics for management and econometrics. 3th ed. Boston: Pws-Kent publishing company

KOHLER, H. (1989): Statistics for business and economics. Glenview, Ill. [etc.]: Scott, Foresman and Co.

WONNACOTT, T.H. & WONNACOTT, R. J. (1990): Introductory statistics for business and economics 4th ed. New York [etc.] : John Wiley & Sons

 

PROGRAM

  1. Introduction to STATA.
  2. Univariate and bivariate analysis with STATA (Descriptive Statistics, Contingency Tables, ANOVA and simple regression).
  3. Multiple Linear regression (OLS regression assumptions, Working with independent qualitative variables, Linearity and Transformations).
  4. Logistic regression.
  5. Other multivariate analysis techniques:
    • Cluster Analysis
    • Factor analysis
    • Structural Equation Models

 

EVALUATION

The system followed in the subject considers the following elements to assess the performance of the students:

  • Assignments: 50%
  • Test: 50%

 To compute the final mark applying the mentioned weights, each part has to earn a minimum mark of 5.