Confidence, Tests, and Probability Models
Quantify uncertainty with confidence intervals, evaluate claims via hypothesis tests, and plan with expected value using binomial/Poisson models.
Learning Objectives
Construct and interpret confidence intervals for means and proportions.
Perform one-/two-sided hypothesis tests and report exact p-values.
Model counts with binomial/Poisson and use EV/variance for planning.
Design studies with power and sample-size considerations.
Lessons
Lesson 5-1
Confidence Intervals & Estimation
Construct confidence intervals for means and proportions, interpret margin of error, and connect to sampling variability.
Lesson 5-2
Hypothesis Testing & Significance
Perform one- and two-sided tests, compute test statistics and p-values, and make data-driven decisions.
Lesson 5-3
Probability Models & Expected Value
Model random processes with binomial/Poisson distributions and apply expected value to real-world planning.
Why This Unit Matters
Reliable Decisions
Intervals and tests formalize evidence so decisions are reproducible.
Risk-Aware Planning
EV/variance quantify outcomes so plans balance reward and risk.
Broader Literacy
Statistical thinking underpins modern science, engineering, and policy.