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Course Syllabus

Master 2021/2022

Introduction to R

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Type: Compulsory course
Area of studies: Finance and Credit
Delivered by: School of Economics and Finance
Where: Faculty of Economics
When: 1 year, 1 module
Mode of studies: distance learning
Open to: students of one campus
Instructors: Petr Parshakov
Master’s programme: Financial Strategies and Analitics
Language: English
ECTS credits: 3
Contact hours: 4

Course Syllabus

Full 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

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

Expected Learning Outcomes

  • Is able to explore dataset.
  • Have skills of data cleaning.
  • Have skills of data visualization.
  • Is able to transform datasets.
  • Know basic data types and R syntax.
  • Know types of data joining.
Course Contents

Course Contents

  • Introduction in R
  • Data manipulation and visualization
Assessment Elements

Assessment Elements

  • non-blocking Self-study work
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
    0.6 * Self-study work + 0.4 * Exam
Bibliography

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
  • 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