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Бакалавриат 2019/2020

Язык R: статистические выводы

Направление: 45.03.03. Фундаментальная и прикладная лингвистика
Когда читается: 4-й курс, 3 модуль
Формат изучения: MOOC
Язык: английский
Кредиты: 3

Программа дисциплины

Аннотация

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data. Instructor - Mine Çetinkaya-Rundel, Associate Professor of the Practice, Department of Statistical Science, Duke University. https://www.coursera.org/learn/inferential-statistics-intro
Цель освоения дисциплины

Цель освоения дисциплины

  • The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data.
Результаты освоения дисциплины

Результаты освоения дисциплины

  • Knows how to set up and perform hypothesis tests, interpret p-values, and report the results of the analysis in a way that is interpretable for clients or the public.
  • Knows how to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest.
Содержание учебной дисциплины

Содержание учебной дисциплины

  • Inferential Statistics
    This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data.
Элементы контроля

Элементы контроля

  • Online course (неблокирующий)
  • Discussion with a HSE instructor (неблокирующий)
Промежуточная аттестация

Промежуточная аттестация

  • Промежуточная аттестация (3 модуль)
    0.3 * Discussion with a HSE instructor + 0.7 * Online course
Список литературы

Список литературы

Рекомендуемая основная литература

  • Pace L., Hlynka M. Beginning R an introduction to statistical programming. New York: Apress, 2012.

Рекомендуемая дополнительная литература

  • Field, A. V. (DE-588)128714581, (DE-627)378310763, (DE-576)186310501, aut. (2012). Discovering statistics using R Andy Field, Jeremy Miles, Zoë Field. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.363067604