Fall 2025 - SDA 100 D100

Data Visualization (3)

Class Number: 7299

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 3 – Dec 2, 2025: Thu, 12:30–2:20 p.m.
    Burnaby

Description

CALENDAR DESCRIPTION:

Introduces the principles and tools of data visualization and visual storytelling with R. Learn foundational and advanced plotting techniques to create impactful visuals and interactive dashboards, transforming raw data into compelling data-driven stories for diverse audiences. Students who have taken ECON 334, POL 390, STAT 240, or STAT 310 first may not then take this course for further credit. Quantitative.

COURSE DETAILS:

Description:

We are living in a technological and data revolution–one that has profound implications for society. Indeed, we have seen the critical role that social media sites like Facebook and Twitter/X have played in shaping recent elections around the globe, including through the spread of disinformation. The data revolution is also ushering in a new era in the search for cures to diseases, while the rise of the Internet and integration of digital technologies into everyday life has generated unprecedented amounts of data on human behaviour, whether through digitized public records, detailed information on consumer habits and preferences, health monitoring, or social media.

This data is easily shared and stored. Moreover, powerful computing tools make it possible to sort through immense volumes of this data to find patterns, answer questions, and solve problems. Because of this, the field of social data analytics is rapidly gaining importance in research, policymaking, and the private sector, and there is a surge in labour market demand for individuals with these critical skills. How can we use this new data to better understand social problems and improve decision-making?

This course provides a hands-on introduction to data visualization and serves as a gateway to social data science more broadly. Students will explore foundational plotting techniques, learn advanced approaches, including geospatial visualization and the creation of interactive charts and dashboards. By the end of the course, students will be equipped to transform data into compelling data-driven stories for diverse audiences. Lectures will focus on learning the fundamental principles and tools in R. Tutorials will focus on applying these tools to real world data, including how they can help us to synthesize and advance knowledge. Through in-class practice, quizzes, and homework projects, students will learn to apply data science techniques to social research.

Course Organization:

The course meets on Mondays, 12:30-1:20, and Thursdays, 12:30-2:20. Students are expected to have done the reading prior to class and be prepared to actively participate in lab tutorials.

 

Grading

  • Homework & Labs 25%
  • Short Quizzes 10%
  • Midterm Exam 20%
  • Final Project 30%
  • Participations & Engagement 15%

Materials

REQUIRED READING:

Required Text(s):


REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

At SFU, you are expected to act honestly and responsibly in all your academic work. Cheating, plagiarism, or any other form of academic dishonesty harms your own learning, undermines the efforts of your classmates who pursue their studies honestly, and goes against the core values of the university.

To learn more about the academic disciplinary process and relevant academic supports, visit: 


RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.