Delivered at:: Department of Sociology

Course type:: Compulsory course

When:: 2 year, 3, 4 module

Instructors

Vólchenko, Olesya

Korsunava, Viyaleta

Shirokanova, Anna

Full Syllabus

Abstract

This course lasts for three years. The 1st year aims at beginners. This year starts from introductory topics (variable types, hypothesis testing, descriptive statistics) to working with some methods (chi-square, t-test, nonparametric statistics, one-way ANOVA, and linear regression). The course covers the building blocks of quantitative data analysis with the aim to train students to be informed producers and consumers of quantitative research. The applied part introduces working in R (RStudio) for calculations and reporting. Prerequisites: understanding key ideas in sampling theory and probabilities. This course is the starting point for social science and humanities students interested in pursuing training in advanced methods of data analysis or planning to use quantitative methods in their own research.

Learning Objectives

develop skills necessary to solve typical data analysis problems on social data in the R software environment

Expected Learning Outcomes

Choose appropriate methods and techniques for certain types of variables and certain aims of the analysis
Conduct statistical analyses in RStudio
Create analytical reports describing all the stages of analysis and interpreting its results
Give meaningful interpretation of statistical results: regression coefficients, tables, plots and diagrams (produced in R)
Perform data transformations
Represent graphically the results of the statistical analyses

Course Contents

Central tendency measures
Chi-square
Two means comparison
One-way ANOVA
Linear regression
Linear regression with multiple predictors

Assessment Elements

Projects
Late submissions are not considered (try us). If you are ill during the project submission, present a medical certificate to get the formula adjusted for you. If you miss more than one project, there might be a makeup assignment. When you submit a project in MS Teams, you must click on the "Turn in" button to complete the submission. All projects are, first, posted to the dedicated channel where they are peer-reviewed, and submitted in the Assignments section by each contributing student. If you have any questions about the project, sign up for a consultation.
In-class activity
Exam
Short tests
MOOC completion
Mid-Term Test

Interim Assessment

2021/2022 4th module
0.05 * Short tests + 0.4 * Projects + 0.2 * Mid-Term Test + 0.1 * In-class activity + 0.1 * Exam + 0.15 * MOOC completion
2022/2023 4th module
2023/2024 3rd module

Bibliography

Recommended Core Bibliography

Denis, D. J. (2016). Applied Univariate, Bivariate, and Multivariate Statistics. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1091881
Tabachnick, B. G., & Fidell, L. S. (2014). Using Multivariate Statistics: Pearson New International Edition (Vol. 6th ed). Harlow, Essex: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1418064

Recommended Additional Bibliography

Agresti, A., & Finlay, B. (2014). Statistical Methods for the Social Sciences: Pearson New International Edition (Vol. Pearson new international ed., 4. ed). Harlow England: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1418314
Crawley, M. J. (2013). The R Book (Vol. Second Edition). Chichester, West Sussex: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=531630
Little, T. D. (2013). The Oxford Handbook of Quantitative Methods, Volume 1 : Foundations. Oxford University Press.
Little, T. D. (2013). The Oxford Handbook of Quantitative Methods. Oxford University Press.

Bachelor’s Programme 'Sociology and Social Informatics'

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Data Analysis in Sociology

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