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
• Part II: Modeling Variation
• segmentChapter 5 - A Simple Model
• segmentChapter 6 - Quantifying Error
• segmentChapter 7 - Adding an Explanatory Variable to the Model
• segmentChapter 8 - Models with a Quantitative Explanatory Variable
• segmentFinishing Up (Don't Skip This Part!)
• segmentResources

list High School / Statistics and Data Science I (AB)

Book
• High School / Statistics and Data Science I (AB)
• College / Statistics and Data Science (ABC)
• High School / Advanced Statistics and Data Science I (ABC)
• College / Advanced Statistics and Data Science (ABCD)
• High School / Statistics and Data Science II (XCD)

Part II: Modeling Variation

In this section of the course we develop the concept of statistical model. We start with the simplest model, sometimes called the “empty model.” From there we move to more complex models.

We create statistical models in order to:

• Explain variation in an outcome variable using one or more explanatory variables, and to better understand the Data Generating Process;

• Predict the values of future observations, or samples;

• Guide changes we can make to improve the outcomes of the system we are studying.