StatPREP Workshops for 2018

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Schedule for Highline College workshop (Seattle) June 15-16

Friday

8:30 am, breakfast

9:00 am, start program

1. Welcome.

2. Examples of in-class lessons centered on data
   • Two-sample t Little App
   • Concept lesson: What’s normal? Background and activity
   • Start with graphics: Randy Pruim’s first second-day-of-class activity using Births in 2015 to introduce visual displays of data
     • Tutorial: Less Volume, More Creativity from eCOTS 2018 (includes material on ggformula)
     • Tutorial: Intro to ggformula
     • Tutorial: Refining plots in ggformula
     • Danny’s notes on plotting
3. Tidy data
   • Notes and group activity
4. Data and statistical graphics: The graphics behind the Little Apps.
   • Tutorial summary
   • Chapter from Statistics for Data Science by Danny Kaplan

12:30 pm Lunch

5. Thinking about lessons. Select three topics from your current stats course that you would like to teach with data. They could be, for example, a technique, theory, or a project.
   • Working with local data
   • Working with Little Apps
6. Learning R: Two tracks
   • Starting R: functions, formulas, and parts of speech notes and quiz and continue on with tidy data frames, graphics for data science, calculating statistics
   • Using RStudio.cloud
7. Exploring statistics using StatPREP materials.
   • Tutorials, which are instructor-oriented, R-based introductions to techniques and concepts.
   • Little Apps

3:15 pm Adjourn

Saturday

8:30 am, breakfast

9:00 am, start program

1. Statistical concepts: Two tracks:
   • Streamlining inference with regression
     • Little app on regression, proportions, one-way ANOVA
     • R tutorial
   • Simulation-based inference:
     • Little apps involving resampling: confidence intervals & proportions
     • R tutorials: sampling, resampling, and shuffling
2. Communicating with your students: Three tracks
   • Setting up a course web site.
   • Writing a learnr tutorial.
     • Tutorial on df_stats()
     • Code for the tutorial
   • Collecting data with your students
     • Globe tossing
     • Hypothesis testing with shuffling
3. Determining lesson-development groups. Homework answers

12:30 pm Lunch

4. Lesson development: Small group activity with two tracks
   • Developing lessons based on Little Apps
   • Developing lessons using R commands.
5. Brief presentations of lessons developed
   • Hartford
     • Data from the island
     • Post-it Notes
     • Hartford Corrections data in HTML and Rmd and the data set … or the rstudio.cloud project
   • St. Paul
     • Support for investment in Saint Paul parks
     • Bayesian analysis
     • Joining data to make maps
6. Going forward … support and staying in touch

3:15 pm, adjourn