Бакалавриат
2026/2027
Бизнес-статистика
ID 1253450
Статус:
Курс обязательный (Международный бизнес)
Где читается:
Высшая школа бизнеса
Когда читается:
1-й курс, 3 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Контактные часы:
48
Course Syllabus
Abstract
The "Business Statistics" course gives students the statistical tools and methods they need to make well-founded business decisions. It covers a range of statistical concepts and methods used to analyse business data. Students will learn to collect, analyse, interpret and present data effectively, so they can draw meaningful conclusions and make data-driven decisions. The course focuses on hands-on use of statistical methods with real business scenarios, so students see how to apply them in areas such as marketing, finance and operations. Students use statistical software to analyse data, which builds their skill in processing and interpreting large datasets. By the end of the course, students should be able to understand statistical reports, spot trends and make data-driven decisions. This prepares them to work in a range of business sectors.
Learning Objectives
- To equip students with the fundamental statistical literacy required to transform raw business data into actionable insights, enabling them to make effective, evidence-based decisions in a variety of professional contexts.
- To develop students' ability to collect, analyze, interpret, and present data effectively, thereby enabling them to identify trends, solve business problems, and make data-informed decisions in key areas
Expected Learning Outcomes
- Define statistics as a science, distinguishing its subject, specific method, and main objectives.
- Explain the role of statistics as a source of reliable data for analyzing the economy and society
- Define and identify a statistical population, and explain the concept of its homogeneity
- List and describe the main stages of statistical research
- Apply the grouping method by classifying data into appropriate types of statistical groupings for a given analytical objective
- Critically select and apply appropriate types of indicators to accurately describe a dataset, justifying their choice based on the data's structure and the research objective
- Decompose a complex economic or social phenomenon into its constituent trends, cyclical patterns, and seasonal variations to diagnose underlying causes and predict short-term behavior
- Quantify overall change in a multifaceted, heterogeneous group (e.g., the cost of living, total business revenue) and analytically attribute this change to the specific influence of individual factors, such as price shifts versus changes in consumption patterns
- Assess the validity, limitations, and potential biases of statistical claims and official economic indicators by evaluating the methods used to construct them
- Diagnose the operational and financial health of an enterprise by synthesizing data on its resources (labor, capital), processes (productivity, turnover), and outcomes (costs, profit), and by attributing strengths and weaknesses to specific functional areas
- Construct and utilize statistical models that represent key economic relationships within a firm
- Evaluate the efficiency and long-term sustainability of an enterprise's use of all its resources
- Synthesize data from national accounts, demographic statistics, and household surveys to analyze how macroeconomic aggregates manifest in and are shaped by microeconomic realities
- Deconstruct official economic narratives by critically evaluating the methodological choices embedded in key indicators
- Choose and apply descriptive statistics and data visualisation methods to analyse business data (including open-source data), and interpret the results to define and solve practical problems.
- Clean, group and carry out an initial analysis of data using modern tools, in order to find trends, structural shifts and anomalies in business indicators.
- Formulate and test statistical hypotheses (including through A/B testing) to assess how effective business decisions are, and correctly interpret p-values, confidence intervals and sampling errors.
- Assess whether sample data are representative, and justify whether conclusions can be generalised to the population in the context of real business research.
- Build and evaluate correlation and regression models to find relationships between business indicators, test whether coefficients are significant, and interpret regression equations for business problems.
- Analyse time series, identify trend and seasonality, and produce short-term forecasts of key metrics (sales, demand, revenue) to support management decisions.
- Apply the index method and factor analysis tools to break down changes in business indicators and justify data-driven management decisions.
- Present analysis results as an analytical memo or presentation with practical recommendations for business, and defend the conclusions in front of an audience.
Course Contents
- Module 1. Fundamentals of Business Data Analysis
- Module 2. Probability Foundations and Statistical Inference
- Module 3. Forecasting and Modelling
- Module 4. Applied Business Analytics and Decision-Making
- Enterprise statistics as a source of information for the market sector of the economy
- Macroeconomic and social statistics. Basic concepts and categories used to construct the system of national accounts.
Interim Assessment
- 2026/2027 3rd module0.4 * Exam + 0.2 * Group project + 0.3 * Seminar assignment + 0.1 * Attendance
Bibliography
Recommended Core Bibliography
- Frederick J Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano, & James E. Witnauer. (2020). Essentials of Statistics for the Behavioral Sciences, Edition 10. Cengage Learning.
- Social-Economic Statistics : Textbook for Academic Bachelor Programs / E. V. Sibirskaya, L. V. Oveshnikova, L. A. Mikheikina [and others]. — Mosco w: UNITY-DANA, 2018. — 159 pp. - ISBN 978-5-238-03059-3. - Текст : электронный. - URL: https://znanium.ru/catalog/product/2223519 (дата обращения: 03.09.2025).
- Нарбут, В. В. Экономическая статистика=Economic statistics : учебник / В. В. Нарбут, В. Н. Салин, Е. П. Шпаковская. — Москва : КноРус, 2023. — 232 с. — ISBN 978-5-406-10947-2. — URL: https://book.ru/book/947677 (дата обращения: 01.07.2026). — Текст : электронный.
Recommended Additional Bibliography
- Нарбут, В. В. Статистика: теория и практика = Statistics: Theory and Practice : учебник / В. В. Нарбут, Е. П. Шпаковская, В. Н. Салин. — Москва : КноРус, 2022. — 389 с. — ISBN 978-5-406-09450-1. — URL: https://book.ru/book/944515 (дата обращения: 01.07.2026). — Текст : электронный.