• Lecture Notes
  • Introductory Lecture 1 Data Types and Data Collection

    with Video , Self-Test , and Self-test Solutions

  • Introductory Lecture 2 Graphical Displays and Measures of Center with Video , Self-Test , and Self-test Solutions

  • Introductory Lecture 3 The Variance and Standard Deviation with Video , Self-Test , and Self-test Solutions

  • Introductory Lecture 4 Percentiles and Boxplots with Video , Self-Test , and Self-test Solutions

  • Lecture 1 Introduction

  • Lecture 2 Chapter 3: Introduction to Probability

  • Lecture 3 Chapter 3: Probability

  • Lecture 4 Chapter 3: Probability; Chapter 4: Discrete Random Variables

  • Lecture 5 Chapter 4: Discrete Random Variables; Chapter 5: Continuous Random Variables

  • Lecture 6 Chapter 5: Continuous Random Variables

  • Lecture 7 Chapter 5: Continuous Random Variables

  • Lecture 8 Poisson and Exponential Random Variables

  • Supplementary notes Chapter 4: Poisson Random Variables

  • Supplementary notes Chapter 5: Linking Poisson and Exponential Random Variables

  • Lecture 9 Chapter 6: Sampling Distributions and the Central Limit Theorem

  • Lecture 11 Chapter 6: Sampling Distributions

  • Supplementary notes Chapter 6: Sampling Distributions

  • Lecture 12 Chapter 7: Confidence Intervals

  • Lecture 13 Chapter 7: Confidence Intervals

  • Lecture 14 Chapter 7: Confidence Intervals; Chapter 8: Hypothesis Tests

  • Lecture 15 Chapter 8: Hypothesis Tests (presently a shell)

  • Lecture 16 Chapter 8: Hypothesis Tests

  • Lecture 17 Chapter 8: Hypothesis Tests

  • Supplementary notes Chapter 8: Testing a proportion (exact test)

  • Lecture 18 Chapter 9: Inference for Two Variables

  • Lecture 19 Chapter 9: Inference for Two Variables

  • Lecture 20 Chapter 8: Power

  • Supplementary notes Chapter 8: Power

  • Lecture 21 Chapter 14: Nonparametric Tests

  • Supplementary notes Chapter 14: Nonparametric Statistics

  • Lecture 23 Chapter 10: Introduction to Linear Models

  • Lecture 24 Chapter 10: ANOVA

  • Supplementary notes Chapter 10: Analysis of Variance

  • Lecture 25 Chapter 11: Introduction to Regression

  • Lecture 26 Chapter 11: Regression

  • Supplementary notes Chapter 11.3: Regression

  • Supplementary notes Chapter 11.4: Regression

  • Lecture 27 Chapter 13: Categorical Data Analysis

  • Lecture 28 Chapter 13: Categorical Data Analysis

  • Supplementary notes Chapter 13: Categorical Data Analysis

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