Bachelor
2024/2025
Information Systems
Type:
Elective course (Sociology and Social Informatics)
Area of studies:
Sociology
Delivered by:
Department of Sociology
When:
1 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Nikita Zubarev
Language:
English
ECTS credits:
8
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
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
- 2024/2025 2nd module0.3 * Homeworks + 0.1 * Midterm 1 + 0.15 * Midterm 2 + 0.2 * Midterm 3 + 0.25 * Report based on given data
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.
- 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
- 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