Economic Statistics

2025/2026

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Economics

Course type:

Compulsory course

When:

1 year, 2 module

Instructors

Гарипова Фарида Габдулхаевна

Rodionova, Tatiana

Khabibullina, Alina

Course Syllabus

Abstract

The primary objective of this course is to equip students with an understanding of how the process of formulating research questions, collecting relevant data, analyzing and visualizing results, and interpreting statistical evidence supports effective problem-solving and strategic decision-making. Students will develop the ability to apply statistical reasoning and quantitative methods in real-world contexts. Emphasis is placed on cultivating practical skills in data literacy, critical thinking, and evidence-based decision-making. The course offers a comprehensive introduction to statistics for students who seek to understand how statistical tools and analytical techniques are used to address real problems, assess alternatives, and support sound analytical decisions—without requiring prior coursework in probability theory.

Learning Objectives

• The course aims to: • Develop students’ ability to identify, collect, and use primary and secondary data sources appropriately, and to correctly interpret and apply statistical information in various contexts; • Teach students how to organize, summarize, and present statistical data clearly and accurately using tables, charts, and graphs; • Enable students to compute and interpret key descriptive measures; • Involve students in the full statistical process — from data exploration and analysis to drawing meaningful conclusions and formulating recommendations; • Engage students in the practical application of statistical methods for decision-making through case studies, problem-solving exercises, and collaborative project work.

Expected Learning Outcomes

• Describe the importance of statistics.
• Differentiate between descriptive statistics and inferential statistics
• Explain the various data types
• Describe variables and types of measurement scales
• Summarize qualitative data by constructing a frequency distribution
• Construct and interpret a pie chart and a bar chart
• Summarize quantitative data by constructing a frequency distribution
• Construct and interpret a stem-and-leaf diagram
• Calculate and interpret measures of central location
• Interpret a percentile and a boxplot
• Calculate and interpret measures of dispersion
• Explain mean-variance analysis and the Sharpe ratio
• Construct and interpret a scatterplot
• Calculate and interpret covariance between two variables
• Calculate and interpret the correlation between two variables

Course Contents

• 1. What is Statistics?
• 2. Generalizing statistical indicators: absolute and relative values. Indexes.
• 3. Presenting Data in Tables and Charts
• 4. Numerical Descriptive measure
• 5. Measures of dispersion / Variation
• 6. Correlation analysis

Assessment Elements

• Quizzes
• Group project
  Work in teams of 5-6 people. Students need to prepare a) Excel file with the data + data visualizations and numerical analysis, b) a presentation that should include the following sections: dataset and variables description, summary statistics and distribution descriptions, analysis to potential research questions. The grade for the assignment is based on the submitted materials and the project defense (answers to questions). Questions may be addressed individually or to the entire team. If a student cannot attend the defense due to illness, they must provide a medical certificate.
• Test
  Final test on the materials covered the whole course with open and closed questions (multiple and single choice questions). The test is carried out in the classroom, in writing. The test is a closed book, closed notes. Using course materials is not allowed.

Interim Assessment

• 2025/2026 2nd module
  0.29 * Group project + 0.28 * Quizzes + 0.43 * Test

Bibliography

Recommended Core Bibliography

• Business statistics : A Decision-Making Approach, Groebner, D. F., 1993

Recommended Additional Bibliography

• Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
• Essentials of business statistics, Jaggia, S., 2014
• Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.
• Inequality, polarization and poverty : advances in distributional analysis, Chakravarty, S. R., 2009

Authors

• Khabibullina Alina Rishatovna
• BRODSKAYA NATALYA NIKOLAEVNA