The aim:
1. Statistical inference for regression models.
2. Applying lineal regression models to cross-sectional data.
3. Applying lineal regression models to time series data.
4. Using logistic model in marketing.
5. Use of a statistical package Gretl.

Acquired knowledge:
1. Confidence intervals and statistical hypotheses.
2. Regression model, the mle and least squares method.

Acquired skills:
1. Formulating and verifying statisitcal hypotheses.
2. Using regression models in empirical relationship studies.

Acquired social skills:
1. Principles of hypothese testing and regression analysis.
2. Basic use of regression analysis in economic studies.

Course contents:
1. Simple and multivariate regression model.
2. Maximum likelihood and least squares estimation method.
3. Testing statistical hypotheses for regression models.
4. Applying regression models to cross sectional and time series data.
5. Logistic model and uplift method.

Recommended reading: 
1. Introductory Econometrics, a Modern Approach, Wooldridge, J, South Western College.
2. Basic Statistics for Business and Economics, Lind, D. and Mason, R., McGraw-Hill.