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Бакалавриат 2024/2025

Статистические методы анализа рынка

Статус: Курс обязательный (Прикладной анализ данных)
Направление: 01.03.02. Прикладная математика и информатика
Когда читается: 4-й курс, 2, 3 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 4

Course Syllabus

Abstract

In this course, we understand market analysis as a set of various probabilistic, statistical, econometric and stochastic methods that help to solve real applied problems. Classical approaches of data analysis do not always work properly in reality. There is a need to explore other methods (often more complex and advanced). We introduce some of such tools which can be applied in practice and, in our humble opinion, are extremely important and useful.
Learning Objectives

Learning Objectives

  • To learn how various advanced probabilistic, statistical, econometric and stochastic techniques can be applied to the real business problems
Expected Learning Outcomes

Expected Learning Outcomes

  • Students will gain ample knowledge of Bootstrap, Welch test, Mann-Whitney test, CUPED, The difference in Difference estimator, Matching, Multiple comparison.
  • Students will gain ample knowledge of Discriminant analysis, LOGIT, PCA, Factor analysis, Cluster analysis, Dendrogramms, Conjoint Analysis and Multidimensional scaling.
  • Students will gain ample knowledge of Sampling, Sample size calculation, Contingency tables, Chi-squared tests, ANOVA, ANCOVA and Partial correlation.
  • a student can perform an A/B test
  • a student can apply a difference-indifference approach
  • a student can apply bootstrap techniques
  • a student can work with logistic regressions (simple, ordered and multinomial)
  • a student can apply non-parametric techniques
  • a student can apply stochastic methods
  • a student can conduct an A/B test
Course Contents

Course Contents

  • A/B testing
  • difference-in-difference approach
  • bootstrap
  • logistic regression (simple, ordered and multinomial)
  • non-parametrics
  • stochastics (Markov models and extreme value analysis)
Assessment Elements

Assessment Elements

  • non-blocking home assignment 1
  • non-blocking midterm 1
  • non-blocking home assignment 2
  • non-blocking midterm 2
  • non-blocking final exam
Interim Assessment

Interim Assessment

  • 2024/2025 3rd module
    0.2 * final exam + 0.15 * home assignment 1 + 0.15 * home assignment 2 + 0.25 * midterm 1 + 0.25 * midterm 2
Bibliography

Bibliography

Recommended Core Bibliography

  • Malhotra, N. K. (2017). Marketing Research. [N.p.]: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1531280

Recommended Additional Bibliography

  • Newbold, P., Carlson, W. L., & Thorne, B. (2013). Statistics for Business and Economics: Global Edition (Vol. Eight edition). Boston, Massachusetts: Pearson Education. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1417883

Authors

  • Абдулхакимов Мухиддин Мураджанович
  • Slabolitskiy Ilya Sergeevich