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Октябрь

Economic Statistics

2018/2019
Учебный год
ENG
Обучение ведется на английском языке
6
Кредиты
Статус:
Курс обязательный
Когда читается:
2-й курс, 1, 2 модуль

Преподаватели

Course Syllabus

Abstract

Mathematical statistics is a branch of mathematics, that studies how to collect, generate, classify and analyze data using the tools of the Theory of probability. The first module introduces methods of descriptive statistics and basic methods of inferential statistics. The second module introduces other methods of statistical data analysis.
Learning Objectives

Learning Objectives

  • introduce students to the basic notions and methods of statistical analysis, which can be applied to obtain optimal solutions in economy and business.
Expected Learning Outcomes

Expected Learning Outcomes

  • Know the basic concepts of economic statistics, statistical methods of collection, processing and analysis, tabular and graphical presentation of results and conclusions
  • Be able to formulate the research problem, find the necessary statistical information for the task, substantiate the methods of analyzing statistical data, analyze the results, obtained by these methods, apply them to make managerial decisions.
  • Be able to collect and process data, effectively using modern computer technologies
Course Contents

Course Contents

  • Mathematical statistics: the subject and method. General information on statistical observation.
  • Statistical data: summarizing, grouping and representation (analytical and graphical); statistical tables.
  • Generalizing statistical indicators: absolute and relative values, average values, structural average values, variance.
  • Selective observation, point and interval estimation
  • Statistical hypothesis testing
  • Statistical hypothesis testing
  • Introductory lesson on working with statistical functions of MS Excel
  • Factor analysis and variance analysis
  • Non-parametric methods of analysis
  • Statistics of relations
  • Other types of statistical analysis: cluster analysis, survival analysis, index analysis
  • Introduction to time series analysis
  • Practical statistical research
Assessment Elements

Assessment Elements

  • non-blocking exam 2
  • non-blocking cum 2
  • non-blocking cum 1
  • non-blocking exam 1
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.6 * cum 1 + 0.4 * exam 1
  • Interim assessment (2 module)
    0.4 * cum 2 + 0.2 * exam 2 + 0.4 * Interim assessment (1 module)
Bibliography

Bibliography

Recommended Core Bibliography

  • Greene, W. H. (2015). Econometric analysis. Slovenia, Europe: Prentice-Hall International. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.1BF5A5CA

Recommended Additional Bibliography

  • Bruce, P. C. (2014). Introductory Statistics and Analytics : A Resampling Perspective. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=923330