Язык R: статистические выводы

Бакалавриат 2020/2021

Статус: Курс по выбору (Фундаментальная и компьютерная лингвистика)

Направление: 45.03.03. Фундаментальная и прикладная лингвистика

Кто читает: Школа лингвистики

Где читается: Факультет гуманитарных наук

Когда читается: 4-й курс, 3 модуль

Формат изучения: с онлайн-курсом

Преподаватели: Ландер Юрий Александрович

Язык: английский

Кредиты: 3

Контактные часы: 2

Full Syllabus Ask Question

Abstract

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

Learning Objectives

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.

Expected Learning Outcomes

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.

Course Contents

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.

Assessment Elements

Online course
Discussion with a HSE instructor
Online course
Discussion with a HSE instructor

Interim Assessment

Interim assessment (3 module)
0.3 * Discussion with a HSE instructor + 0.7 * Online course

Bibliography

Recommended Core Bibliography

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

Recommended Additional Bibliography

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

Course Syllabus