Кто читает:: Департамент социологии

Статус:: Курс обязательный

Когда читается:: 2-й курс, 3, 4 модуль

Преподаватели

Ткачева Татьяна Юрьевна

Цигеман Элина Сергеевна

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.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. The 2nd year aims at intermediate-level students. This year starts from introductory topics (data preparation, visualization, basic statistical tests) to working with more advanced methods of data analysis (interaction effects in linear regression, GLM, factor analysis). The course aims to develop quantitative data analysis skills required to understand and perform independent research. The applied part includes working in R (RStudio). The 3d year aims at upper-intermediate level students.

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
Data quality. Main issues with data
Missings treatment
Decision trees
Cluster analysis
Advanced regression techniques
Multilevel regression
3rd year topics
4th year topics

Assessment Elements

In-class participation and practice
Mid-term test
Final exam (blocking)
Group projects

Interim Assessment

2023/2024 4th module
0.3 * Final exam (blocking) + 0.3 * Group projects + 0.2 * In-class participation and practice + 0.2 * Mid-term test
2024/2025 4th module
1 * 2023/2024 4th module
2025/2026 3rd module
1 * 2023/2024 4th 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.

Бакалаврская программа «Социология и социальная информатика»

Контакты

Коронавирус Live

Data Analysis in Sociology