Bachelor 2023/2024

Information Systems

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Type: Elective course (Sociology and Social Informatics)

Area of studies: Sociology

Delivered by: Department of Sociology

Where: Saint-Petersburg School of Social Sciences

When: 1 year, 1, 2 module

Mode of studies: offline

Open to: students of one campus

Instructors: Nikita Zubarev

Language: English

ECTS credits: 8

Contact hours: 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

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

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

Interim Assessment

• 2023/2024 2nd module
  0.3 * 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