Applied Statistics

2024/2025

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Economics

Course type:

Compulsory course

When:

2 year, 4 module

Instructors

Гарипова Фарида Габдулхаевна

Zhuravleva, Tatyana

Course Syllabus

Abstract

This discipline belongs to the professional cycle (Major) disciplines (B.PC), its basic part (B.PC.B). The study of this discipline is based on the following disciplines:•economic theory,•mathematics,•theory of probability and mathematic statistics.To master the discipline students must have the following knowledge and competencies:•Able to learn, acquire new knowledge, skills, including in a field other than professional (MC-1).•Is able to solve problems in professional activity on the basis of analysis and synthesis (MC-3).•Is able to work with information: find, evaluate and use information from different sources necessary for solving scientific and professional tasks (including systematic approach) (CB-5).•Is able to choose tools for information processing in accordance with the scientific task, analyze the results of calculations and justify the obtained conclusions (PC-32).The main provisions of the discipline should be used in the further study of the disciplines:•econometrics,•institutional economics, •economics of the public sector,•international economics,•labor economics.

Learning Objectives

• The objectives of the discipline "Applied Statistics" are: • gaining students' knowledge of the properties of statistical data; • to acquire students' knowledge of the methods of descriptive statistical analysis; • to study the basic methods of regression analysis, their advantages and disadvantages.

Expected Learning Outcomes

• be able to perform inference to test the significance of common measures such as means and proportions and conduct chi-squared tests of contingency tables
• be able to summarise the ideas of randomness and variability, and the way in which these link to probability theory to allow the systematic and logical collection of statistical techniques of great practical importance in many applied areas
• be able to collect, process, and aggregate statistical data
• be able to routinely apply a variety of methods for explaining, summarising and presenting data and interpreting results clearly using appropriate diagrams, titles and labels when required. Can find data in open databases
• be able to use correlation analysis and simple linear regression and know when it is appropriate to do so

Course Contents

• 1. Subject of statistics
• 2. Descriptive statistics
• 3. Probability theory: revision
• 4. Normal distribution and sampling
• 5. Confidence intervals
• 6. Hypothesis testing
• 7. Contingency tables and chi-squared test
• 8. Sampling design
• 9. Linear regression and least squares method

Assessment Elements

• Test
• Final test
• Homework: project

Interim Assessment

• 2024/2025 4th module
  0.4 * Final test + 0.3 * Homework: project + 0.3 * Test

Bibliography

Recommended Core Bibliography

• Introduction to econometrics, Stock, J. H., 2008

Recommended Additional Bibliography

• Anonymous. (1985). The Visual Display of Quantitative Information. By Edward R. Tufte. (Cheshire, Conn.: Graphics Press, 1983. Pp. 197. $34.00.). American Political Science Review, 2, 623.
• Steven Feiner, S. Card, J. Mackinlay, & G. Robertson. (2009). 1812. (Popularized by E Tufte, The Visual Display of Quantitative Information). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.CF0DC995

Authors

• BRODSKAYA NATALYA NIKOLAEVNA
• Zhuravleva Tatiana Leonidovna