36-315: Statistical Graphics and Visualization
Lecture 1
Meghan Hall
Department of Statistics & Data Science
Carnegie Mellon University
May 21, 2021
Teaching team
Instructor: Meghan Hall
Grad TA: Galen Vincent
Undergrad TAs
Office hours TBD
Course objectives
- Create statistical graphics.
Course objectives
Create statistical graphics.
Understand the fundamentals of data and reproducible data analysis.
Course objectives
Create statistical graphics.
Understand the fundamentals of data and reproducible data analysis.
Write about statistical graphics.
Course objectives
Create statistical graphics.
Understand the fundamentals of data and reproducible data analysis.
Write about statistical graphics.
Speak about statistical graphics and data analyses.
Course objectives
Create statistical graphics.
Understand the fundamentals of data and reproducible data analysis.
Write about statistical graphics.
Speak about statistical graphics and data analyses.
Assess and critique statistical graphics.
Course tools
R & RStudio
Course tools
R & RStudio
ggplot2 and related packages
Course tools
R & RStudio
ggplot2 and related packages
R Markdown
Course components
Course components
Lectures
Course components
Lectures
Labs
Course components
Lectures
Labs
Homework
Course components
Lectures
Labs
Homework
Code style
Code style
Code must be written with the tidyverse style guide
Ignore section II, focus on I.2, I.4, I.5
It will match lecture notes, lab notes, etc.
You can use the R package styler if you want
Course components
Lectures
Labs
Homework
Code style
Course components
Lectures
Labs
Homework
Code style
Graphics discussion
Course components
Lectures
Labs
Homework
Code style
Graphics discussion
Midterm
Course components
Lectures
Labs
Homework
Code style
Graphics discussion
Midterm
Group project
Course components
Various logistics
Course website(s)
Various logistics
Course website(s)
Piazza
Various logistics
Course website(s)
Piazza
Communication
Various logistics
Course website(s)
Piazza
Communication
Office hours
Various logistics
Course website(s)
Piazza
Communication
Office hours
Extensions
Various logistics
Course website(s)
Piazza
Communication
Office hours
Extensions
Regrades
Various logistics
Course website(s)
Piazza
Communication
Office hours
Extensions
Regrades
Integrity
Why do we visualize data?
| x | y |
|---|---|
| 55.3846 | 97.1795 |
| 51.5385 | 96.0256 |
| 46.1538 | 94.4872 |
| 42.8205 | 91.4103 |
| 40.7692 | 88.3333 |
| 38.7179 | 84.8718 |
| 35.6410 | 79.8718 |
| 33.0769 | 77.5641 |
| 28.9744 | 74.4872 |
| 26.1538 | 71.4103 |
Why do we visualize data?
| Mean of x | Mean of y |
|---|---|
| 54.26327 | 47.83225 |
Why do we visualize data?
| Mean of x | Mean of y |
|---|---|
| 54.26327 | 47.83225 |
| SD of x | SD of y |
|---|---|
| 16.76514 | 26.9354 |
Why do we visualize data?
| Mean of x | Mean of y |
|---|---|
| 54.26327 | 47.83225 |
| SD of x | SD of y |
|---|---|
| 16.76514 | 26.9354 |
| Variable | Min | Max |
|---|---|---|
| x | 22.3077 | 98.2051 |
| y | 2.9487 | 99.4872 |
Why do we visualize data?
Why do we visualize data?
Explore
Diagnose
Explain
By the end of the class
You can...
Ask relevant questions from data
Know which types of visualizations are appropriate for your data
Know which types of visualizations are appropriate for your audience
Create plots that are
Effective in their properties
Elegant & aesthetically-pleasing
Some golden rules of graphs
Don’t add complexity without a good reason.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Don’t distort data, intentionally or not.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Don’t distort data, intentionally or not.
Be mindful of the data-to-ink ratio.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Don’t distort data, intentionally or not.
Be mindful of the data-to-ink ratio.
All axes, labels, etc. should have real titles, not code variable names.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Don’t distort data, intentionally or not.
Be mindful of the data-to-ink ratio.
All axes, labels, etc. should have real titles, not code variable names.
Always strive for clarity.
Some golden rules of graphs
Don’t add complexity without a good reason.
Everything (everything!) must be readable.
Don’t distort data, intentionally or not.
Be mindful of the data-to-ink ratio.
All axes, labels, etc. should have real titles, not code variable names.
Always strive for clarity.
Titles, subtitles, and captions should add information.
Upcoming
Lecture 2 on Monday May 24
grammar of graphics and tidyverse principles
Lab 1 on Tuesday May 25
be on the lookout for a survey about times