1. Introduction to Statistics. Overview. The Nature of Data. Uses and Abuses of Statistics. Design of Experiments. 2. Describing, Exploring, and Comparing Data. Overview. Summarizing Data with Frequency Tables. Pictures of Data. Measures of Center. Measures of Variation. Measures of Position. Exploratory Data Analysis (EDA). 3. Probability. Overview. Fundamentals. Addition Rule. Multiplication Rule: Basics. Multiplication Rule: Complements and Conditional Probability. Probabilities Through Simulations. Counting. 4. Probability Distributions. Overview. Random Variables. Binomial Probability Distributions. Mean, Variance, and Standard Deviation for the Binomial Distribution. The Poisson Distribution. 5. Normal Probability Distributions. Overview. The Standard Normal Distribution. Nonstandard Normal Distributions: Finding Probabilities. Nonstandard Normal Distributions: Finding Values. The Central Limit Theorem. Normal Distribution as Approximation to Binomial Distribution. Determining Normality. 6. Estimates and Sample Sizes. Overview. Estimating a Population Mean: Large Samples. Estimating a Population Mean: Small Samples. Determining Sample Size. Estimating a Population Proportion. Estimating a Population Variance. 7. Hypothesis Testing. Overview. Fundamentals of Hypothesis Testing. Testing a Claim about a Mean: Large Samples. Testing a Claim about a Mean: Small Samples. Testing a Claim about a Proportion. Testing a Claim about a Standard Deviation or Variance. 8. Inferences from Two Samples. Overview. Inferences about Two Means: Independent and Large Samples. Inferences about Two Means: Matched Pairs.