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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

• 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

• 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

• 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

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

Промежуточная аттестация

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

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