## Course Outline

• segmentGetting Started (Don't Skip This Part)
• segmentStatistics and Data Science: A Modeling Approach
• segmentPART I: EXPLORING VARIATION
• Part 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 - Models with a Quantitative Explanatory Variable
• segmentPART III: EVALUATING MODELS
• segmentChapter 9 - Distributions of Estimates
• segmentChapter 10 - Confidence Intervals and Their Uses
• segmentChapter 11 - Model Comparison with the F Ratio
• segmentChapter 12 - What You Have Learned
• segmentFinishing Up (Don't Skip This Part!)
• segmentResources

# Part I: Exploring Variation

Statistics is the study of variation. It is the tools and concepts we have invented over time to help us learn from variation. If variation didn’t exist, then we wouldn’t need statistics. But variation is everywhere. If everyone who took a particular drug got well, and everyone who didn’t died, we wouldn’t need statistics. But that’s usually not what happens. Usually some people who take the drug get well, but some don’t. Some people who don’t take the drug get well anyway. It’s not that easy to tell whether the drug really cures the ailment, or if the cure just happened by chance. Statistics is designed to help us make sense of such situations. It is made up of a set of concepts and tools that have evolved over hundreds of years to help us find patterns in, and make sense of, variation. (For an excellent history of statistical ideas see Weisberg, Herbert I. (2014). Willful Ignorance: The Mismeasure of Uncertainty. Hoboken, NJ: Wiley.)