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Магистратура 2021/2022

Введение в статистику

Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Направление: 01.04.02. Прикладная математика и информатика
Когда читается: 1-й курс, 1 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Преподаватели: Воробьева Марья Дмитриевна
Прогр. обучения: Прикладная статистика с методами сетевого анализа
Язык: английский
Кредиты: 3
Контактные часы: 28

Course Syllabus

Abstract

The word statistics scares many students. This course is intended for those students who are not confident in their knowledge and abilities on statistics. The course starts with the most basic concepts about sampling and distributions and ends with more advanced concepts about hypotheses and their testing. These topics will help students in more complex courses in the programme.
Learning Objectives

Learning Objectives

  • to give students the opportunity to get acquainted with the basic concepts of statistics
  • to teach how to use statistical terms correctly and work with basic statistical concepts.
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to estimate the mean and variance of a sample
  • be able to explain the rejection of statistical hypotheses
  • be able to explain the use of different methods in relation to a certain measurement scale
  • be able to formulate null and alternative statistical hypotheses
  • know the difference between different measurement scales
  • know which charts are suitable for which type of data
Course Contents

Course Contents

  • The Where, Why, and How of Data Collection
  • Graphs, Charts, and Tables—Describing Your Data
  • Describing Data Using Numerical Measures
  • Introduction to Probability
  • Discrete Probability Distributions
  • Introduction to Continuous Probability Distributions
  • Introduction to Sampling Distributions
  • Estimating Single Population Parameter
  • Introduction to Hypothesis Testing
  • Estimation and Hypothesis Testing for Two Population Parameters
  • Hypothesis Tests and Estimation for Population Variances
  • Analysis of Variance
Assessment Elements

Assessment Elements

  • non-blocking Tests
    There will be three tests during the course. They are based on lecture as well as reading materials. Each test is assigned to chapters in the main course book.
  • non-blocking Final test
    The final test includes 10 multiple choice questions about all topics studied during the course.
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
    0.4 * Final test + 0.6 * Tests
Bibliography

Bibliography

Recommended Core Bibliography

  • Agresti, A. (2017). Statistics: The Art and Science of Learning From Data, Global Edition. Pearson.

Recommended Additional Bibliography

  • James T. McClave, & Terry Sincich. (2013). Statistics: Pearson New International Edition. Pearson.