1. Probability distributions and why they are important
  2. Confidence intervals and presidential elections
  3. Hypothesis Testing changes in the Average or Percentage
    • You made a change to a process but did you make a difference?
    • How confident are you that you made a difference?
    • What is the risk?
  4. Hypothesis Testing with Two Populations
    • Comparing two sales territories, two distribution centers, two plants, etcetera
  5. Hypothesis Testing changes in Variation
  6. Hypothesis Testing changes in Market Share
  7. Experimental Design / Analysis of Variance: Single Factor
  8. Experimental Design / Analysis of Variance: Multiple Factors
    • Which factor(s) affected performance
    • Are there interactions amongst factors
  9. Simple Regression
    • Correlation of two variables
  10. Multiple Variable Regression
    • Predict the future
    • Which variables improve or hurt performance
  11. Building Good Regression Models
    • What makes a good predictive model
  12. Logistic Regression
    • Which variables improve or hurt the “odds” of winning
    • Predicting winning proposals