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DA380: Sequential Analysis and Applications

Real-world, application-first course for DA students at Denison University.

Tip

What is Sequential Analysis?

  • A real-time decision-making approach that analyzes data as it is collected
  • Uses a flexible stopping rule based on pre-defined thresholds

Why Use Sequential Analysis?

  • Cost-efficient –Minimizes unnecessary data collection
  • Faster conclusions – Maximizes data utilization for early termination
  • Adaptable – Integrates new data dynamically without restarting the study

Applications of Sequential Analysis

  • Stock market change-point detection
  • Pandemic outbreak monitoring
  • Online A/B testing
  • Adaptive clinical trials
  • Industrial quality control
  • And more…
Week Topic External Readings Deliverables
1 Why Sequential Lessons from World War II Statisticians Coding Warmup: Simulation on CLT
2 Light foundations Reviews on Probability Simulation Study: Sequential Confidence Interval
3 Purely Sequential A general sequential fixed-accuracy confidence interval estimation methodology for a positive parameter: illustrations using health and safety data Deer Sampling Practice
4 Sequential Probability Ratio Test Is trust in government really declining? Shiny App on SPRT
5 Control Chart Guide to Using Excel Control Charts Sample Size Calculation with G*Power
6-7 Sequential Adaptive Design in Clinical Trials Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine Shark Tank: Design the Experiment for Riverside Genral Hospital
8 Change Point Detection Real Time Anomaly Detection CPD Activity
9-10 Swining Door Algorithm and Bayesian Online Detection A note on Bayesian Online Changepoint Detection Code Practice: CPD
11-12 Sequential AB Test Simple Sequential AB Test Simulation Study: Type I Error Inflation and mSPRT