Programming in R

2018/2019

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Дирекция по онлайн-обучению

Статус:

Курс по выбору

Когда читается:

2-й курс, 2 модуль

Course Syllabus

Abstract

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

Learning Objectives

• how to program in R, to use R for effective data analysis
• how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts

Expected Learning Outcomes

• reading data into R and accessing R packages
• programming in R, writing R functions
• debugging, profiling R code
• organizing and commenting R code

Course Contents

• Background, Getting Started, and Nuts & Bolts
  the history of R and S, the basic data types in R, the functions for reading and writing data
• Programming with R
  control structures and functions, Programming with R
• Loop Functions and Debugging
  aspects of R make R useful for both interactive work and writing longer code
• Simulation & Profiling
  the basis for doing simulation studies

Assessment Elements

• тест
  after attending the MOOC it is required to present the final results (certificate/another document)
• самостоятельная работа
  after attending the MOOC it is required to present the final results (certificate/another document)

Interim Assessment

• Interim assessment (2 module)
  0.7 * самостоятельная работа + 0.3 * тест

Bibliography

Recommended Core Bibliography

• Spector, P. (2008). Data Manipulation with R. New York: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=229058

Recommended Additional Bibliography

• Introduction to R. (2016). France, Europe: HAL CCSD. https://doi.org/10.1051/eas/1677002