Бакалавриат
2025/2026
Информационные системы
Лучший по критерию «Новизна полученных знаний»
Статус:
Курс по выбору (Социология и социальная информатика)
Кто читает:
Департамент социологии
Где читается:
Санкт-Петербургская школа социальных наук
Когда читается:
1-й курс, 1, 2 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
8
Контактные часы:
64
Course Syllabus
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
- HomeworksCollections of exercises aimed at preparing students for midterms
- Midterm 2
- Midterm 3
Interim Assessment
- 2025/2026 2nd module0.25 * 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.