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Обычная версия сайта
Магистратура 2020/2021

Модели маркетинга (продвинутый уровень)

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Статус: Курс по выбору (Менеджмент и аналитика для бизнеса)
Направление: 38.04.02. Менеджмент
Когда читается: 2-й курс, 1 модуль
Формат изучения: без онлайн-курса
Прогр. обучения: Менеджмент и аналитика для бизнеса
Язык: английский
Кредиты: 3

Course Syllabus

Abstract

The primary focus of this course if on quantitative models that can be used by managers to support marketing decisions. In addition to having conceptual skills, modern managers must increasingly master techniques of data-driven decision modeling to do strategic planning based on information from corporate information systems as well as external data sources. This course teaches how to apply econometric, machine learning and optimization techniques to marketing problems.
Learning Objectives

Learning Objectives

  • Choose methods adequately corresponding to the objectives of a research project
  • Collect, store, process and analyze data according to high standards
  • Conduct empirical business research using modern analytic software tools
  • Develop and apply new research methods
  • Solve managerial problems using best practices of data analysis using modern computational tools
Expected Learning Outcomes

Expected Learning Outcomes

  • Choose methods adequately corresponding to the objectives of a research project
  • Collect, store, process and analyze data according to high standards
  • Conduct empirical business research using modern analytic software tools
  • Develop and apply new research methods
  • Solve managerial problems using best practices of data analysis using modern computational tools
Course Contents

Course Contents

  • Optimization modeling for Marketing
  • Advanced Excel functions for analyzing marketing data
  • Econometric modeling of scanner sales data
Assessment Elements

Assessment Elements

  • non-blocking Empirical case studies solved in class:
  • non-blocking Kahoot
  • non-blocking Midterm exam based on Data camp
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.25 * Empirical case studies solved in class: + 0.25 * Exam + 0.25 * Kahoot + 0.25 * Midterm exam based on Data camp
Bibliography

Bibliography

Recommended Core Bibliography

  • Quirk, T. J., & Rhiney, E. (2016). Excel 2016 for Marketing Statistics : A Guide to Solving Practical Problems. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1261494

Recommended Additional Bibliography

  • Chapman, C., & Feit, E. M. (2019). R For Marketing Research and Analytics (Vol. Second edition). Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2093001