Statistical Data Visualization

STAT 479 Spring 2021

Kris Sankaran (University of Wisconsin-Madison)

The official syllabus, which gives requirements, learning objectives, and grading mechanisms, is available here. This website only includes links to the reading and lecture content – the course structure is mapped out fully on the Canvas homepage.

Readings

Week Topic Reading
1
Marks and Channels (1) Introduction to Data Science: Chapter 7
(2) Data Types, Graphical Marks, and Visual Encoding Channels
1 (optional) (1) Data Humanism
2
Faceting and Layout (1) Introduction to Data Science: Chapter 9.1 - 9.3, 9.7
(2) Multi-View Composition
3
Interaction (1) Visualization Analysis and Design: Chapter 12.1 - 12.3, 13.1 - 13.3
(2) Interaction
3 (optional) Up and Down the Ladder of Abstraction
4
Data Wrangling R for Data Science: Chapter 12
5
Quality Checking (1) Getting Started with naniar
(2) Profiler: Integrated Statistical Analysis and Visualization for Data Quality Assessment
6
Time Series Forecasting Principles and Practice: Chapter 2
7
Geographic Data Geographic Data in R: Chapter 2
8
Network Data (1) Visualization Analysis and Design: Chapter 9
(2) Modern Statistics for Modern Biology: Chapter 10.1 - 10.2
9
Clustering (1) Intro to Data Science: Chapter 34
(2) Superheat Vignette (2, 3 & 6)
(3) Cluster Analysis of Genomic Data
10
Dimensionality Reduction I (1) Beginner’s Guide to Dimensionality Reduction
(2) PCA and UMAP with tidymodels and #TidyTuesday cocktail recipes
(3) Understanding UMAP
11
Dimensionality Reduction II (1) Text mining with R: Chapter 6
(3) Visualizing the structure of RNA-seq expression data using grade of membership models
12
Model Building (1) Partial-dependence Profiles
(2) Visualization in Bayesian workflow
13
Visualizing Deep Learning Models (1) Four Experiments in Handwriting with a Neural Network
(2) Visualizing what convnets learn
13 (optional) Automation Makes Us Dumb
14
Conclusion (1) 655 Frustrations of Doing Data Visualization
(2) Tukey, Design Thinking, and Better Questions
14 (optional) A Brief History of Data Visualization

Lectures

Notes are listed here. Source code and links to recorded videos are listed at the top of each set of lecture notes.