1 
Title of the course 
Statistical methods in economics

2 
Year and speciality

3, Mathematics (economic activity)

3 
Semester 
6 
4 
Number of credits

3 
5 
Lecturer

Bakhtin Victor Ivanovich 
6 
Objectives of the course 
Enhancement of the mathematical scope, acquaintance with new methods of mathematical reasoning, possession of methods of statistical analysis of economic problems
As a result of the course study a student have to be able: — to choose an adequate statistical model describing a certain economic object or phenomenon; — to perform analysis of an economic object or forecasting of an economic process within the framework of the chosen model by means of the “Statistica” computer package; — to construct the point and interval estimates for parameters; — to verify statistical hypotheses; — to construct tests for statistical check of hypotheses by methods of multivariate statistical analysis; — to perform analysis and make forecasts for time series.

7 
Prerequisites 
Linear algebra, functional analysis, probability theory

8 
Contents of the course 
1. Statistical estimation of parameters 1.1. The subject of mathematical statistics and econometrics. 1.2. Basic notions of the mathematical statistics. 1.3. Empirical distributions and sample estimates. 1.4. Quantiles and plevels. 1.5. The method of moments for construction of estimates. 1.6. The Rao–Cramer inequality. 1.7. The efficient and asymptotically efficient estimates. 1.8. The maximumlikelihood method. 1.9. Conditional expectations. 1.10. Conditional distributions. 1.11. Bayesian estimation. 1.12. Sufficient statistics. 1.13. The interval estimation of parameters. 2. Statistical check of hypotheses. 2.1. Basic notions of statistical check of hypotheses. 2.2. The Neiman–Pearson decision rule. 2.3. A simple hypothesis check against a composite alternative. 2.4. Goodnessoffit tests. 2.5. The likelihood ratio test for composite hypotheses. 2.6. Bayesian decision rules.

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Recommended literature 
Basic. 1. Bakhtin, V.I. An introduction to applied statistics. Lecture course. Part I. Mathematical statistics. — Minsk, BGU, 2011 (in Russian). 2. Bakhtin, V.I. An introduction to applied statistics. Lecture course. Part II. The methods of applied statistics. — Minsk, BGU, 2012 (in Russian). 3. Kharin, Yu.S.; Zhuk, E.E. Mathematical and applied statistics. — Minsk, BGU, 2005 (in Russian) 4. Aivazian, S.A.; Mkhitarian, V.S. Applied statistics. Elements of econometrics. V. 1, 2. Moscow, 2001 (in Russian).
Auxiliary 1. Borovkov, A.A. Mathematical statistics. — Moscow, Nauka, 1984 (in Russian). 2. Lagutin, M.B. Visualizing mathematical statistics. — Moscow, Binom, 2009 (in Russian). 3. Mardas, A.N. Econometrics. — St. Petersburg, 2004 (in Russian). 4. Orlov, A.I. Econometrics. — Moscow, Ekzamen, 2004 (in Russian). 5. Mynbayev, K.; Lemas, A. Econometrics. — Almaty, 2004 (in Russian).
The fulltext lectures are available at 
10 
Teaching methods 
Lectures, exercises, laboratory works, supervised independent work Examples of laboratory works are available at 
11 
Language

Russian 
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Conditions (requirements), running control 
– test; – laboratory work 
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Form of assessment

Test 