Statistics B — Probability Models and Statistical Inference is the second semester of a full-year statistics course for grades 11-12, following Statistics A. It is built on California’s Probability and Statistics standards (PS.1-PS.19) and the California CCSS Statistics and Probability standards.
Four units: Continuous Distributions and Sampling Distributions, Estimating with Confidence, Testing Claims: Significance Tests, and Chi-Square, Regression Inference and the Capstone Study. Students discover the central limit theorem by simulating samples from real NOAA weather records, build confidence intervals and significance tests by hand and with free tools, and finish with a full inference study they design, carry out, write up and defend.
Sources: OpenStax Statistics (CC BY-NC-SA 4.0; referenced, not reproduced) as the reference text; public federal datasets (U.S. government works, public domain); SLS-written lessons and tasks. Any dataset that is not from a named public source is labeled illustrative. Tools: CODAP, spreadsheets, PhET and GeoGebra Probability, all free. Python in a free JupyterLite notebook is an optional route.
Optional certification links: spreadsheet statistical functions (NORM.DIST, T.INV, CHISQ.TEST and others) line up with part of the Microsoft Office Specialist Excel Associate objectives, and the optional Python route supports part of the Python Institute PCEP exam. These links are optional. The course does not prepare students for either exam on its own.
Curriculum
- 4 Sections
- 20 Lessons
- Lifetime
- Unit 1: Continuous Distributions and Sampling Distributions5
- Unit 2: Estimating with Confidence5
- Unit 3: Testing Claims: Significance Tests5
- Unit 4: Chi-Square, Regression Inference and the Capstone Study5
Instructor
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