Data Visualization (302-0-20)
Instructors
Arend Matthew Kuyper
IPR, 2040 Sheridan Road, Evanston
Meeting Info
TBA: TBA
Overview of class
Visualizing data plays an important role in both data exploration and presenting analytic results. Quality data visualizations help analysts better understand and effectively communicate their work. This course will help students develop the necessary knowledge and skills to produce quality data visualizations.
Students will learn how to construct quality data visualizations using R and RStudio. The course will focus on principles and techniques used to create static visualizations. The course will also provide an introduction to interactive visualizations. These skills will be developed through project/lab-based learning. A significant proportion of the course will be dedicated to a large-scale project.
Registration Requirements
Students should have an introductory understanding of statistics (i.e. STAT 202-0 or 210-0) and since it is an accelerated course, familiarly with R and RStudio is highly recommended.
Learning Objectives
1. Identify, define, and describe the nine core concepts of the grammar of graphics that underlie static data visualizations.
2. Select and construct appropriate data visualizations for data exploration and presentation.
3. Build a series of data visualizations to tell a truthful and compelling story with data.
4. Develop skills necessary to be an independent and active learner --- especially as it relates to coding.
Teaching Method
The course is designed to guide students through an accelerated 5-week, asynchronous version of Data Visualization (STAT 302-0), which will typically require a minimum 16-20 hours per week to complete the assigned course work. The course will be delivered through lesson modules comprised of readings and/or videos with associated assessments such as reading checks and lab assignments that will need to be completed in accordance with the due dates listed in the syllabus. A typical week will have 4 modules each with various assessments to be completed. While the course material will be delivered asynchronously, students will be required to meet published deadlines throughout all 5 weeks of the course.
The course will have a discussion board and students will be encouraged to engage with each other by asking and answering questions. The instructor will also be actively engaged through the course discussion board and will provide virtual office hours each Friday morning from 9 am - 12 noon.
Evaluation Method
There will be a final project in place of a written exam. We will also evaluate progress throughout the session using project/lab-based learning assignments.
Class Materials (Required)
1. Free online textbook, ggplot2: Elegant Graphics for Data Analysis, 3rd Edition: https://ggplot2-book.org/index.html
2. Free online textbook, Fundamentals of Data Visualization: https://clauswilke.com/dataviz/
3. Free online textbook, Mastering Shiny: Build Interactive Apps, Reports & Dashboards Powered by R: https://mastering-shiny.org/index.html
4. Free statistical software R (https://cran.rstudio.com/)
5. Free integrated development environment software RStudio (https://www.rstudio.com/). Think of R as the car engine needed to power and run everything while RStudio is the steering wheel/dashboard that we use to run and control the car.
Class Materials (Suggested)
Grammar of Graphics (Statistics and Computing) by Leland Wilkinson. Springer-Verlag New York, 2005. ISBN: 9780387245447 (Print) 9780387286952 (Online). Northwestern students can access a free pdf version through the library.
Class Attributes
Formal Studies Distro Area
Asynchronous:Remote class-no scheduled mtg time