## Course Outline

• segmentGetting Started (Don't Skip This Part)
• segmentStatistics and Data Science: A Modeling Approach
• segmentPART I: EXPLORING VARIATION
• segmentChapter 1 - Welcome to Statistics: A Modeling Approach
• segmentChapter 2 - Understanding Data
• segmentChapter 3 - Examining Distributions
• segmentChapter 4 - Explaining Variation
• segmentPART II: MODELING VARIATION
• segmentChapter 5 - A Simple Model
• segmentChapter 6 - Quantifying Error
• segmentChapter 7 - Adding an Explanatory Variable to the Model
• segmentChapter 8 - Digging Deeper into Group Models
• segmentChapter 9 - Models with a Quantitative Explanatory Variable
• segmentPART III: EVALUATING MODELS
• segmentChapter 10 - The Logic of Inference
• segmentChapter 11 - Model Comparison with F
• segmentChapter 12 - Parameter Estimation and Confidence Intervals
• segmentFinishing Up (Don't Skip This Part!)
• segmentResources

### list High School / Advanced Statistics and Data Science I (ABC)

Book
• High School / Advanced Statistics and Data Science I (ABC)
• High School / Statistics and Data Science I (AB)
• High School / Statistics and Data Science II (XCD)
• College / Statistics and Data Science (ABC)
• College / Advanced Statistics and Data Science (ABCD)
• College / Accelerated Statistics and Data Science (XCDCOLLEGE)
• Skew the Script: Jupyter

## 1.6 Goals of This Course

Well, we didn’t even let you get through the introduction without doing some actual R coding! Doing and thinking—these are the main things you should be filling your time with as you go through this course. Doing without thinking would reduce you to just rote memorization of procedures. Thinking without doing would be awfully boring—you would miss the exciting part!

Our goals for this course are as follows:

• First, to learn how to analyze data, using R. We want you to end up well on your way to being truly competent with data.

• Second, to understand the core concepts of the domain of statistics—the ideas that will help you make sense of the analyses you produce.

• Third, to prepare you to learn more about statistics in the future. Statistics is a big field. Knowing a little is still useful, but you should feel ready to keep learning after you finish this course.

### It’s Not About Memorizing R Code

Even though you will learn a lot about R, there are literally thousands of functions in R, more than anyone could remember. Even advanced users of R can’t remember it all.

As you go through the textbook, you may find it helpful to keep track of new R functions in a notebook. We’ve also provided an R Cheatsheet that you can mark up as you go through the course. It has all the commands we use in this course organized on two pages. You should download it from the list below and keep it handy.