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Course Syllabus

2021/2022

Basic Statistics and Introduction into "R"

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Type: Optional course (faculty)
Delivered by: School of Sociology
Where: Faculty of Social Sciences
When: 1 module
Open to: students of all HSE University campuses
Instructors: Anna Almakaeva
Language: English
ECTS credits: 4
Contact hours: 28

Course Syllabus

Full Syllabus

Abstract

The course aims to provide students with an understanding of key concepts and methods of modern statistical data analysis. It gives an overview of the skills necessary for conducting independent research with quantitative survey data, using R software. The course also puts these skills into the broader academic context by reviewing how statistics are used in published scientific journal articles. This course includes an online course "Introduction to R" at DataCamp (https://www.datacamp.com/). DataCamp provides free access to its courses for educators upon request.
Learning Objectives

Learning Objectives

  • Provide students with an understanding of the basic concepts of statistical analysis
  • Provide students with an understanding of the basic principles of R programming
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to choose correct statistical methods and procedures according to the research questions and the level of measurement, read and transform data in R Studio, calculate basic statistics in R Studio, interpret and present results of in oral and written form
  • have skills in using R Studio for reading and transforming data, calculation of basic statistics and interpretation of results
  • know the key concepts of basic statistics, main principles and procedures R programming, main procedures of data transformation and statistical analysis in R Studio.
Course Contents

Course Contents

  • Introduction into R
  • Introduction into sociological inquiry
  • Measurement
  • Data transformation
  • Descriptive statistics
  • Visualization
Assessment Elements

Assessment Elements

  • non-blocking Home assignment
    Grading criteria:1) Correct method of data analysis. 2) Correct R function. 3) Correct interpretation.
  • non-blocking Reading previous research
  • non-blocking Essay
  • non-blocking Exam
    The task of the first reexam is similar to the first exam. Students will have 3 hours to do it. The second reexam is similar to the first one. The weight of the reexam in the final grade is 0.3.
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
    0.1 * Reading previous research + 0.35 * Essay + 0.25 * Home assignment + 0.3 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Field, A. V. (DE-588)128714581, (DE-627)378310763, (DE-576)186310501, aut. (2012). Discovering statistics using R Andy Field, Jeremy Miles, Zoë Field. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.363067604
  • Hadley, W. (2016). Ggplot2 : Elegant Graphics for Data Analysis. New York, NY: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1175341

Recommended Additional Bibliography

  • Hatekar, N. (2010). Principles of Econometrics : An Introduction (using R). New Delhi, India: SAGE Publications India Pvt., Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=354910
  • Layder, D. (1998). Sociological Practice : Linking Theory and Social Research. London: SAGE Publications Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=775757