Objective: 
The course acquaints students with methods of data presentation and data analytic techniques based on statistical inference.

The aim:
To acquaint students with methods of data presentation and description.
Presentation basic notions of probability.
To acquaint students with basic methods of statistical inference.

Acquired knowledge:
Knowledge of descriptive statistics methods.
Knowledge of basic probability.
Knowledge of basic statistical inference methods.

Acquired skills:
Collecting, describing and analyzing data.
Using basic statistical inference methods.

Developed reflection:
Ability of defining the problem and finding adequate methods to solve it.

Assessment: 
The final grade consists of: exam ( 40% ), term papers ( 40% ), class activity ( 20% ).

Contents: 
Descriptive statistics, methods of displaying data.

Probability models, parameters of probability distribution.

Random sample, statistical model.

Statistical inference for one and two populations.

Analysis of two-way tables. Inference for regression.

Recommended reading: 
Basic statistics for business & economics,  Douglas A. Lind, William G. Marchal, Samuel A. Wathen. The McGraw-Hill Companies. McGraw-Hill Higher Education, Boston, 2006.

Complete business statistics, Aczel, Amir D. Homewood, IL, Boston, 1989.