June 9-10, 2017

## Outline of the workshop

### Shop

Today and tomorrow morning: go through some tutorials

• learn a little data science
• learn a little R
• gather some ideas

### Work

Tomorrow afternoon

• Work in groups to create a draft "lesson" you can use in one of your classes

## How do we define success?

1. You begin to get connected to the hub community.

2. You make a good first step toward using computational tools in your teaching.

3. You leave here having learned something of value to you (idea generation).

4. You have an enjoyable time. (This is supposed to be fun.)

5. We get some feedback on our materials and this StatPREP.

• You are the first of 8 StatPREP cohorts.

• This is our pilot, so your feedback really helps us.

## One-stop Shopping statprep.org

But then select this menu item

## Feedback/Questions

2. Find a shoulder surfer.

3. Type in this Google Doc

R is one tool for working with data, but many of the things we will talk about are more general than R and apply equally to other ways of working with data.

• state of the art (high quality, wide scope)
• widely used in academia and industry
• excellent data visualization
• reproducible workflow tools (including the tutorials we will be using)
• free!
• the presenters know it

## What we hope you will learn about R

• R is not that scary (but it helps to be selective)

• You don't need to be an expert to get started
• R is very powerful and will grow with you and your students

• R is not the only way to do these things

• Cognitative skills can transfer over to other systems (but details with change)