Лучший по критерию «Новизна полученных знаний»

Кто читает:: Департамент социологии

Статус:: Курс по выбору

Когда читается:: 1-й курс, 1, 2 модуль

Преподаватели

Букина Арина Алексеевна

Зубарев Никита Сергеевич

Full Syllabus Ask Question

Abstract

The course covers theoretical and practical basics of working with quantitative data in the social sciences. We will start with the foundations of interacting with Excel, namely spreadsheet structure and basic formulas. During more advanced sessions we will study logic functions, pivot tables, and text data. A significant part of the course will be devoted to the programming language R. We will study different types and classes of objects within R as well as math and logical operators. Data subsetting in base R will be complemented by data manipulation and aggregation with tidyverse. The course will also introduce students to data visualisation with ggplot2 and tidyverse packages. Our last meetings will focus on a brief overview of several advanced R packages.

Learning Objectives

Explain the place of a person in the Information System
Introduce students to the data analysis tools such as Excel and R
Understand how the concept of Information Systems can be applied to social sciences

Expected Learning Outcomes

Able to run basic functions in Excel
Able to use Latex for making a presentation or short report
Know basic principles of programming in the framework of working with R
Students are familiar with the underlying logic of the syntax of the programming language R.
Students are able to prepare html reports on their analyses using Rmarkdown.
Students are able to perform simple and complicated mathematical and logical operations using R
Students know and understand basic classs of data in R.
be able to perform exploratory data analysis in R: frequencies, shares, means, variances, correlations, etc.
be able to clean, recode, transform, subset, and merge your data using base R tools and tidyverse
be able to import external data sets into R
be able to create effective data visualizations using ggplot2
to know and differentiate between the types of measurement scales used in data analysis.
to know the goals of quantitative data analysis in contemporary sociology
be able to install R and Rstudio on your computer
be familiar with the interface of Rstudio
be able to format Word documents to satisfy basic requirements of university level papers
be able to use shortcuts to effectively navigate MS Excel
to know the syntax of basic Excel functions
be able to apply basic MS Excel functions for the purposes of calculating descriptive statistics
be able to create pivot tables and several types of plots using MS Excel
be able to apply MS Excel functions for the purposes of text data manipulation
be able to apply stringr and tidytext packages for the purposes of text data manipulation and calculating text level statistics

Course Contents

Introduction to Information Systems:
Introduction to Excel and Word / Latex:
Advanced analysis in Excel:
Introduction to R & Rstudio:
Data manipulation using Rstudio:

Assessment Elements

Report based on given data
Midterm 1
Homeworks
Collections of exercises aimed at preparing students for midterms
Midterm 2
Midterm 3

Interim Assessment

2025/2026 2nd module
0.25 * Report based on given data + 0.15 * Midterm 2 + 0.1 * Midterm 1 + 0.3 * Homeworks + 0.2 * Midterm 3

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.
Kabacoff, R. (DE-588)14294372X, (DE-576)350576106. (2011). R in action : data analysis and graphics with R / Robert I. Kabacoff. Shelter Island, NY: Manning. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.347663451
R for data science : Import, tidy, transform, visualize, and model data, Wickham, H., 2017
Robert I. Kabacoff. (2015). R in Action : Data Analysis and Graphics with R: Vol. Second edition. Manning.
Wickham, H., & Grolemund, G. (2016). R for Data Science : Import, Tidy, Transform, Visualize, and Model Data (Vol. First edition). Sebastopol, CA: Reilly - O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1440131
Долгих, Е. А., Анализ данных с MS Excel : учебник / Е. А. Долгих, Л. С. Паршинцева. — Москва : КноРус, 2025. — 151 с. — ISBN 978-5-406-14052-9. — URL: https://book.ru/book/956305 (дата обращения: 09.12.2025). — Текст : электронный.
Мхитарян В.С., Шишов В.Ф., Козлов А.Ю. - Анализ данных в MS Excel - 978-5-906923-26-4 - КУРС - 2025 - https://znanium.ru/catalog/product/2192632 - 2192632 - ZNANIUM
Роберт, И. R в действии. Анализ и визуализация данных в программе R : руководство / И. Роберт, Кабаков , перевод с английского Полины А. Волковой. — Москва : ДМК Пресс, 2014. — 588 с. — ISBN 978-5-97060-077-1. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/58703 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

Бабешко Л.О., Орлова И.В. - Эконометрика и эконометрическое моделирование в Excel и R - 978-5-16-020683-7 - ИНФРА-М - 2025 - https://znanium.ru/catalog/product/2186880 - 2186880 - ZNANIUM
Бельчикова, О. Г. Основы математической статистики. Выполнение расчетов в среде MS Excel : учебно-методическое пособие / О. Г. Бельчикова. — Барнаул : АГАУ, 2025. — 72 с. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/505155 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Authors

ZUBAREV NIKITA SERGEEVICH
MOREVA IULIIA EVGENEVNA

Бакалаврская программа «Социология и социальная информатика»

Контакты

Коронавирус Live

Information Systems