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Regular version of the site

Programming in R

2019/2020
Academic Year
ENG
Instruction in English
5
ECTS credits
Delivered at:
Department of Innovation and Business in Information Technologies
Course type:
Elective course
When:
1 year, 2-4 module

Instructor

Программа дисциплины

Аннотация

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. This is blended course.
Цель освоения дисциплины

Цель освоения дисциплины

  • To equip students with knowledge how to program in R and how to use R for effective data analysis.
Результаты освоения дисциплины

Результаты освоения дисциплины

  • Install and configure the software required for the statistical programming environment
  • Configure statistical programming software
  • Understanding how to use R for efficient data analysis;
  • Understand critical programming language concepts
  • Should make use of R loop functions and debugging tools
  • Collect detailed information using R profiler
Содержание учебной дисциплины

Содержание учебной дисциплины

  • Background, Getting Started, and Nuts & Bolts
    This unit covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story
  • Programming with R
    Welcome to Unit 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
  • Loop Functions and Debugging
    We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice
  • Simulation & Profiling
    This unit covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R III
Элементы контроля

Элементы контроля

  • Экзамен в формате теста (неблокирующий)
  • Online course attendance (неблокирующий)
Промежуточная аттестация

Промежуточная аттестация

  • Промежуточная аттестация (4 модуль)
    0.4 * Online course attendance + 0.6 * Экзамен в формате теста
Список литературы

Список литературы

Рекомендуемая основная литература

  • Practical foundations for programming languages, Harper R., 2013
  • The art of R programming : a tour of statistical software design, Matloff N., 2011