Lecture
Number of hours:  2h X 8 weeks = 16 hours (1 semester)

Laboratory
Number of hours:  2h X 7 weeks = 14 hours (1 semester)

Objective: 
Learning methods of descriptive statistics.
Use of a statistical package Gretl.
Basic notions of probability and risk.
Statistical inference and basic data analysis methods.
Regression analysis of economic and business data.

Assessment: 
Written examination
Laboratory assignments ( 40 % ), final examination ( 60% )

Prerequisites: 
introductory statistics and calculus

Contents: 
Principal data presentation and data analytic techniques based on statistical inference. Understanding its range of applications in business, finance and management. Preparing, presenting and analyzing data with a statistical package Gretl.

Lectures
1. Descriptive statistics.
2. Introduction to GRETL.
3. Probability, random variable, expectation, variance.
4. Confidence intervals.
5. Testing hypotheses.
6. Linear regression.

Recommended reading: 

• Lind, D. and Mason, R. Basic Statistics for Business and Economics. McGraw-Hill, 2006.
• Wooldridge, J. Introductory Econometrics a Modern Approach. Thomson 2006.
• Gretl User’s Guide, provided with Gretl, 2015.