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Магистратура 2024/2025

Анализ временных рядов

Направление: 01.04.02. Прикладная математика и информатика
Когда читается: 2-й курс, 1, 2 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Прогр. обучения: Прикладная статистика с методами сетевого анализа
Язык: английский
Кредиты: 6
Контактные часы: 40

Course Syllabus

Abstract

This course is about quantitative methods, namely statistics, applied to social sciences. Specifically, we will focus on certain statistical competencies that help evaluate processes over time. I expect you to understand the basics of statistics you’ve learned previously in this course; everything else we will learn in this class. As you will see, we will use a lot of real-world datasets, and I am concerned more with your understanding on how statistic works as opposed to memorizing the formulas. This class will be unique in a sense that I will bring a lot of non-statistical material to help you understand the world of decision sciences.
Learning Objectives

Learning Objectives

  • The course gives students an important foundation to develop and conduct their own research as well as to evaluate research of others.
Expected Learning Outcomes

Expected Learning Outcomes

  • Be able to present and/or interpret data in tables and charts.
  • Be able to understand and apply descriptive statistical measures to real-life situations.
  • Be able to understand and apply probability distributions to model different types of social processes.
  • Be able to understand the meaning and use of longitudinal models.
  • Have an ability to forecast future numbers based on historical data.
  • Have an ability to resolve problems and recognize the most common decision errors and make tough decisions in a competent way.
  • Have an ability to use computer software to perform statistical analysis on data (specifically, STATA).
  • Know modern applications of longitudinal analysis.
  • Know the theoretical foundation of longitudinal analysis.
  • Know the variety of time-series models that are available to analyze real-life problems, starting with the simple OLS regression and ending with highly advanced models.
Course Contents

Course Contents

  • Introduction to the Framework of longitudinal data analysis
  • Basics of Time Series I
  • Basics of Time Series II
  • ARIMA
  • Advanced time-series models I
  • Advanced time-series models II
  • Advanced time-series models III
  • Advanced time-series models IV
Assessment Elements

Assessment Elements

  • non-blocking Homework Assignment
  • non-blocking Homework assignments
Interim Assessment

Interim Assessment

  • 2024/2025 2nd module
    0.5 * Homework Assignment + 0.5 * Homework assignments
Bibliography

Bibliography

Recommended Core Bibliography

  • Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting (Vol. Second edition). Hoboken, New Jersey: Wiley-Interscience. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=985114
  • Taris, T. (2000). A Primer in Longitudinal Data Analysis. London: SAGE Publications Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=251795
  • Tsay, R. S. (2010). Analysis of Financial Time Series (Vol. 3rd ed). Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=334288

Recommended Additional Bibliography

  • Beran, J. (2017). Mathematical Foundations of Time Series Analysis : A Concise Introduction. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1741935
  • Franses, P. H., & Paap, R. (2004). Periodic Time Series Models. Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.oxp.obooks.9780199242030
  • Palma, W. (2016). Time Series Analysis. Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1229817

Authors

  • Klimov Ivan Aleksandrovich
  • BOLDYREVA LYUBOV VLADIMIROVNA
  • Павлова Ирина Анатольевна