Master
2020/2021
Introduction to R
Type:
Bridging course (Financial Strategies and Analytics)
Area of studies:
Finance and Credit
Delivered by:
School of Economics and Finance
When:
1 year, 1 module
Mode of studies:
distance learning
Instructors:
Petr Parshakov
Master’s programme:
Financial Strategies and Analitics
Language:
English
ECTS credits:
3
Contact hours:
2
Course Syllabus
Abstract
The course “Introduction to R” is designed to provide students with basic knowledge of in R, free software environment for statistical computing and graphics. The course begins with an introduction to basics of R programming language, data types and importing dataset in different formats. Then students will learn how to explore, clean and prepare data for further analysis. The final part of the course is devoted to techniques of data visualization using R. The course is supported by online platform for education DataCamp (www.datacamp.com). Students are expected to watch online lectures and complete assignments using the platform. Some lectures and final examination are provided by lecturers of National Research University Higher School of Economics.
Learning Objectives
- Know basic syntax of R programming language.
- Import data, explore and clear it.
- Have skills of data manipulation and visualization.
Expected Learning Outcomes
- Know basic data types and R syntax.
- Know types of data joining.
- Is able to transform datasets.
- Have skills of data visualization.
- Is able to explore dataset.
- Have skills of data cleaning.
Course Contents
- Introduction in R1. Basics of R, data types and importing. 2. Exploring and cleaning data.
- Data manipulation and visualization3. Data manipulation and joining with dplyr and intermediate operations in R. 4. Visualization with package ggplot2.
Bibliography
Recommended Core Bibliography
- Boehmke, B. C. (2016). Data Wrangling with R. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1331500
- Rahlf, T. (2017). Data Visualisation with R : 100 Examples. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1377904
Recommended Additional 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