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Высшая школа экономики
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Course Syllabus

Бакалавриат 2023/2024

Прикладная статистика

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус: Курс по выбору (Международный бакалавриат по бизнесу и экономике)
Направление: 38.03.01. Экономика
Кто читает: Департамент экономики
Где читается: Санкт-Петербургская школа экономики и менеджмента
Когда читается: 2-й курс, 4 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для всех кампусов НИУ ВШЭ
Преподаватели: Гарипова Фарида Габдулхаевна, Роспускова Ольга Дмитриевна, Рубцова Софья Валентиновна, Холодилин Константин Аркадьевич
Язык: английский
Кредиты: 3
Контактные часы: 36

Course Syllabus

Full 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 mathematical 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

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 disad-vantages.
Expected Learning Outcomes

Expected Learning Outcomes

  • Justifies the plan of data search for statistical research of real economic situation, forms the system of initial indicators, prepares the data matrix according to the set analytical task, masters the skills of material structuring, checks information from different sources for methodological comparability
  • Can find data in open databases
  • Can meet the requirements for written work
  • Demonstrates the ability to identify the cause-and-effect relations of indicators on the basis of firm reports, and to build a suitable model on this basis.
  • Can make cross-country comparisons
  • Can use different application data pro-cessing packages
  • Can collect, process, and aggregate statistical data
Course Contents

Course Contents

  • Subject matter and method of statistics. General information about statistical observation
  • Summary statistics
  • Statistical study of relationships
  • Sampling and parameter estimation
  • Confidence intervals
  • Tests of statistical significance
  • Linear regression and least squares method
Assessment Elements

Assessment Elements

  • non-blocking Tests
    individual work carried out in LMS 10 minutes during lecture
  • non-blocking Review
    review of outher group's project in small groups of up to 5 persons
  • non-blocking Final test
    multiple-choice test
  • non-blocking Research project
    projects carried out in small groups of up to 5 personas
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.3 * Final test + 0.3 * Research project + 0.1 * Review + 0.3 * Tests
Bibliography

Bibliography

Recommended Core Bibliography

  • Introduction to econometrics, Stock, J. H., 2003
  • Прикладная статистика : Учебник, Орлов, А.И., 2006

Recommended Additional Bibliography

  • Corbett, J. (2002). Edward Tufte, The Visual Display of Quantitative Information, 1983. CSISS Classics. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.ADE6E165
  • 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

  • KHOLODILIN KONSTANTIN ARKADEVICH
  • BRODSKAYA NATALYA NIKOLAEVNA