2024/2025
Basics of R Syntax
Type:
Mago-Lego
Delivered by:
Department of Educational Programmes
When:
1 module
Open to:
students of one campus
Instructors:
Elen Yusupova
Language:
English
ECTS credits:
3
Contact hours:
6
Course Syllabus
Abstract
This course is designed to help students with no prior computer programming experience learn to think computationally and write code to solve problems using R-language. This course will cover the basics of computing and procedural programming, including mathematical, relational, and logical operators, variables and variable types, the basics of style and commenting, iterative solutions, arrays, matrices and their applications, sorting and searching algorithms, elements of string processing, structures, ways to correctly store and represent information. Each topic is illustrated with a set of real-world examples.
Learning Objectives
- The goal of the course is to introduce students to fundamentals in using R. The primary objective of the course is providing students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal for analyzing the data during their education and later, in their career. The secondary objective is to show examples and real researches in which programming skills were applied in order to speed up the data processing
Expected Learning Outcomes
- Students know the basic types of objects used in R
- Students can perform basic mathematical and logical operations with basic types of objects in R
- Students know the structure and types of loops in R
- Students can carry out a full cycle of data pre-processing operations in R
- Students can use basic R tools to visualize data
- Students can create data frames and load data frames into R.
- Students can operate the data frame data type in R: add and delete columns in a data frame, filter and aggregate data frames, merge data frames and reshape a data frame (convert from wide to long representation and vice versa).
Course Contents
- Introduction to R and R-Studio software, acquaintance with the logic of the R language
- Basic types of R objects
- Basic operations on R objects
- Data Frames
- Basics of data visualization in R
Assessment Elements
- Completion of the course
- Quiz scoreAverage score for all quizzes presented in the course
Bibliography
Recommended Core Bibliography
- An introduction to R : a programming environment for data analysis and graphics, Venables, W. N., 2009
- Long, J. D., & Teetor, P. (2019). R Cookbook : Proven Recipes for Data Analysis, Statistics, and Graphics: Vol. Second edition. O’Reilly Media.
- R Cookbook : Proven recipes for data analysis, statistics, and graphics, Teetor, P., 2011
- R в действии : анализ и визуализация данных в программе R, Кабаков, Р. И., 2014
Recommended Additional Bibliography
- Введение в статистическое обучение с примерами на языке R, Джеймс, Г., 2016