Schedule

Contents

• Introduction and Univariate Descriptive Statistics
  • Some Famous Data Sets and Questions
  • Some Basic Concepts
    • Population and Sample
    • Parameters and Statistics
    • Types of Statistics
    • Inferential Statistics
    • Categorical and Numerical Variables
    • Continuous and Discrete Data
    • Univariate, Bivariate, and Multivariate Data
    • The Concept of ``Distribution''
  • Describing One Sample or Population
    • Graphically
    • Numerical Descriptive Statistics
  • Computer Laboratory
  • Concept Lab
• Univariate and Bivariate Descriptive Statistics
  • Percentiles
  • Boxplots
  • Normal Quantile Plots
  • Chebychev and Empirical Rules
  • Z-Scores
  • Bivariate Data
    • Scatterplots
    • Correlation
    • Least Squares Line
    • Coefficient of Determination
  • Computer Lab
  • Concept Lab
• Probability, Random Variables, and the Binomial Distribution
  • Probability
    • Experiments and Events
    • Properties of Probability
    • Some Set Theory
    • Conditional Probability and Independence
    • The Equally Likely Case
    • Relative Frequency Interpretation of Probability
  • Random Variables
    • Mean and Variance of Random Variables
  • Some Discrete Distributions
    • The Binomial Distribution
    • The Hypergeometric Distribution
    • The Negative Binomial Distribution
    • The Poisson Distribution
  • Computer Lab
  • Concept Lab
• Normal Distribution, Sampling Distribution of a Statistic
  • The Normal Curve
    • How Mean and Variance Relate to Curve
    • Finding Areas and Quantiles for Z Curve
  • Sampling Distributions
    • Statistics and Random Samples
    • Sampling Schemes and Inferences from Samples
    • The Central Limit Theorem
    • Normal Approximation to Binomial
    • The Transformed Statistics: Z, t, , F
    • Sampling Distributions of the Transformed Statistics
  • Computer Lab
  • Concept Lab
• Exam 1 and Point and Interval Estimation
  • Point Estimation
    • Point Estimators for Different Situations
    • Properties of Point Estimators
    • Minimum Variance Unbiased Estimation
  • Confidence Intervals
  • Sample Size Determination
    • Estimating with a % confidence interval of length 2B
    • Estimating with a % confidence interval of length 2B
  • Computer Lab for Week 6
  • Concept Lab for Week 6
• Testing Statistical Hypotheses
  • Heuristic Introduction to Hypothesis Testing
    • Null and Alternative Hypotheses
    • Type I and Type II Errors
    • Review: Hypothesis Testing Facts
  • General Method for Hypothesis Testing
  • Reporting the p-value of a test
  • Formulas
  • Computer Lab
  • Concept Lab
• Exam 2 and One-way ANOVA
  • Introduction to ANOVA
  • One-way ANOVA
    • The Model
    • The ANOVA Table
  • Computer Lab for Week 10
  • Concept Lab for Week 10
• Two-way ANOVA and Nonparametric Inferences
  • Two-way ANOVA
    • The Additive Model
    • Two-way ANOVA with Interaction
  • Nonparametric (Distribution-Free) Inferences
    • Introduction to Nonparametric Inferences
    • The Sign Test for Paired Data
    • The Wilcoxon Signed-Rank Test for Paired Data
    • The Wilcoxon Rank-Sum (Mann-Whitney) Test for Two Independent Samples
    • The Kruskal-Wallis Test for K Independent Samples
  • Computer Lab
  • Concept Lab
• Inferences for Simple Linear Regression and Correlation
  • The Simple Linear Regression
    • The Model
  • Point Estimates of Parameters of the Model
  • Inferences for Regression Parameters
  • Inferences for Population Correlation Coefficient
  • Residual Plots and Regression Assumptions
  • Computer Lab
  • Concept Lab
• Categorical Data Analysis
  • Comparing More Than Two Proportions
  • One Categorical Variable
  • Goodness of Fit Testing
  • Inference for Two-Way Tables
    • Descriptive Tables
    • Models and Hypotheses
    • First Model for Tables
    • Second Model for Tables
    • Expected Counts
    • Significance Tests
    • Summary
  • Computer Lab
  • Concept Lab
• About this document ...

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