preparation

Wed Jan 24th

• Install either R or RStudio on your laptop. Ideally, but not essentially, bring your laptop to class.
• Be ready to talk about your preparation for the semester and what you'd like to accomplish.

Mon Jan 29th

• No specific prep for today, but there's quite a bit for Wedensday that you can get started on.

Wed Jan 31st

• Try to work through the first lab here called "Intro to R and RStudio" (if you're not using RStudio, getting it all working in plain R is fine).
• Read through Chapter 1 of the text as far as the end of Section 1.2. There are video links. I haven't watched them, but if you think you might prefer watching videos to reading give them a try. I'm curious what you think.
• Read Storks Deliver Babies ( \( p = 0.008 \) ) by Matthews. Don't worry about the math bits and the jargon---we'll understand it all by the end of the semseter---but focus on the text and the discussion.

Mon Feb 5th and Wed Feb 7th

Do as much as you can for Monday and at least have started all of the pieces for then.

• Move onto the second lab here called Introduction to Data. Don't worry about the plotting commands too much (alternatively, work on trying to do those bits using ggplot instead).
• Reading from the book: the rest of Chapter 1. Sections 1.3 and 1.6 are the most important ones.
• Start learning ggplot2. There are some good places to start linked from the resources page and I'll keep adding more. If you search and find something yourself that works well, let me know and I'll add it to the resources page.
• Making good graphs:
  • 7 tips from flowingdata.com
  • A Duke library guide to graphing
  • Data looks better naked, the first of a series.

This passed through my facebook feed, uncritically (it seemed) shared by friends.

Thoughts?

Mon Feb 12th and Wed Feb 14th

• Homework assignment due this week: be working on that.
• Data Viz readings. Browse the following, follow links, etc.
  • ACCENT principles for graphs
  • Junkcharts
  • Information is Beautiful
• Specific visualisations, for class on Monday and beyond:
  • FlowingData's income use chart(s)
  • Climate Change Escalator
  • Election Map
  • Gun deaths
  • Fatalities by Career and Baby Boomers Describe Themselves (scroll down a little to find them).
  • Spaceships
  • Big Mac Index
  • How Dreamy is Matt Damon? (scroll down for graph).
• Keep playing with R and ggplot2 (you can take this as read for the rest of the semester: you'll always be able to improve and it'll always be a good use of time to do so).
• Either:
  • Theory branch: Delve less into the visualisations and work through some of Chapter 2 of OpenIntro Stats.
  • Visualisation branch: Read some of the more substantial theory about visualisations. There are some books on the reserve shelf (Cairo's "The Truthful Art" especially recommended) or see what you find online. If it's appropriate for you, look particularly for theories of visualisation that are specific to your academic field or some issue you care about.

Mon Feb 19th and Wed Feb 21st

• Before Monday's class, email me a link to a bad data visualisation you've found (according to the parameters discussed in class). Prize available!
• Read 3.1 and 3.2 of OpenIntro Stats on normal distributions.
• For Monday: Get a draft of the form in place on Google Drive (Project Manager is KJ).
• Keep on with the theory/visualisation mentioned last week (and that we didn't talk about then).

Mon Feb 26th and Wed Feb 28th

• Big topic for this week is Chapter 4 of the book on the fundamentals of making inferences. Make sure you have had a good attempt to read and work through as much of it as possible for Monday and come with questions.
• There's an assignment due on Friday this week. Working on that is probably a good idea.

Mon Mar 5th and Wed Mar 7th

• Finish Chapter 4.
• Work through the first 3 sections of the probability notes on the closed resources page (and the 4th too, if you're having fun).
• It's another assignment week: work on that.
• Sections 5.1 to 5.3 of the text (for Wed).
• Start thinking about what project work you'd like to do.
• The Simpson's Paradox demo we saw with on Monday. Play a bit more.

Mon Mar 26th and Wed Mar 28th

• Catch up on any missing assignment work.
• Think about your project: we'll talk about them all on Wednesday and start then start working on them in earnest.

Mon Apr 2nd and Wed Apr 4th

• Work on projects.
• On Monday, we'll decide what to shoot for on Wednesday depending on the Assessment Taskforce work.
  • Update: Read Section 5.5 of OpenIntro Stats on ANOVA.

Mon Apr 9th and Wed Apr 11th

• Work on projects: plan to talk about what you've been doing on either Monday or Wednesday.
• The two articles I mentioned in class on the 4th: Cocaine Use in Schools and ... I'm still looking for the other one. Later: I still haven't found it but the internet meandering did turn up this, which I thought sounded fun. I'll order the book for the library.
• Work on the assignment that's due on 12th April.
• Read 6.1 and 6.2 from OpenIntro Stats.

Mon Apr 16th and Wed Apr 18th

• Work on projects. There will be class time available for talking about it, if that's useful to you (official in-class updates due next week).
• Read 6.3 and 6.4 from OpenIntro Stats on the \( \chi^2 \) distribution/test.
• Not necessary for this week, but we'll be reading all of Chapter 7 on linear regression. Feel free to get started, especially if you think this might be a useful tool for the project.
• Read several papers/articles listed under Weeks 8 and 9 of the Calling Bullshit syllabus and/or listen to this Radiolab podcast and/or read about funnel plots.

Mon Apr 23rd and Wed Apr 25th

• Your project work should be in full swing. Plan on sharing a significant progress update with the class on either Monday or Wednesday.
• Chapter 7 of OpenIntro Stats. I hope we can complete all this theory this week. That's why it's just projects and this for this week.

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