Statistical Inference

Course Outline

Chapter 1

• Coin tosses and probabilistic events

Chapter 2

• From probability to statistical inference

Chapter 3

• Roundup of key concepts in statistical inference
  • Significance level
  • Confidence level
  • Confidence interval

Chapter 4

• Diagnostic tests
  • Confusion matrix
  • Beta
  • Selectivity and specificity
  • Statistical power
  • Effect size
  • Measuring success when incidence rates are low: precision and recall
  • Practical Predictive Value (PPV)

Chapter 5

• Reading and understanding Ioannidis' article "Why Most Published Research Findings are False".

Chapter 6

• Application of concepts to polling design and results (random versus systematic error)
• How to distinguish data reporting from data analysis (most reports just tell you the percentage of this or that - which is much less than what you really need to know)