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8:30 am, breakfast

9:00 am, start program

Welcome.

- 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

- Two-sample t
- Tidy data
- Notes and group activity

- Data and statistical graphics: The graphics behind the Little Apps.

12:30 pm Lunch

- 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

- 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

- Exploring statistics using StatPREP materials.
- Tutorials, which are instructor-oriented, R-based introductions to techniques and concepts.
- Little Apps

3:15 pm Adjourn

8:30 am, breakfast

9:00 am, start program

- 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

- Streamlining inference with regression
- Communicating with your students: Three tracks
- Setting up a course web site.
- Writing a
`learnr`

tutorial. - Collecting data with your students

- Determining lesson-development groups. Homework answers

12:30 pm Lunch

- Lesson development: Small group activity with two tracks
- Developing lessons based on Little Apps
- Developing lessons using R commands.

- 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

- Hartford
- Going forward … support and staying in touch

3:15 pm, adjourn