Basic Statistics and Introduction into "R"

Master 2021/2022

Category 'Best Course for Career Development'

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Type: Compulsory course (Comparative Social Research)

Area of studies: Sociology

Delivered by: School of Sociology

Where: Faculty of Social Sciences

When: 1 year, 1 module

Mode of studies: distance learning

Online hours: 8

Open to: students of all HSE University campuses

Instructors: Anna Almakaeva

Master’s programme: Comparative Soсial Research

Language: English

ECTS credits: 4

Contact hours: 28

Full Syllabus Ask Question

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

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

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

Introduction into R
Introduction into sociological inquiry
Measurement
Data transformation
Descriptive statistics
Visualization

Assessment Elements

Home assignment
Grading criteria:1) Correct method of data analysis. 2) Correct R function. 3) Correct interpretation.
Reading previous research
Essay
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

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

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

Authors

ALMAKAEVA ANNA MIKHAYLOVNA

Course Syllabus