Public learning track
Conditional Probability, Tree Diagrams, and Bayes' Theorem
11th Grade · Math · Open Global Math
7 lessons
Goal
Evaluate conditional probabilities, test for statistical independence, and compute revised probabilities using the Law of Total Probability and Bayes' Theorem.
Featured Diagrams
The Definition and Formula of Conditional Probability
7 lessons
0 of 7 done
- 1The Definition and Formula of Conditional ProbabilityUp nextStart
- 2Calculating Conditional Probabilities from Contingency TablesPremiumNot started yet
- 3Formal Tests for Statistical IndependenceNot started yet
- 4Using Tree Diagrams to Calculate P(A|B)Not started yet
- 5The Law of Total ProbabilityNot started yet
- 6Bayes' Theorem: Inverting Conditional ProbabilitiesNot started yet
- 7Medical Testing, Sensitivity, Specificity, and False PositivesNot started yet
Standards Covered
- OGM.12.STA.2Open Global Math Standards 2026™ · Math · Level 12 / High School 3 (Age 16) · Grade 11Solve probability problems using combinatorics (permutations, combinations, fundamental counting principle), sample spaces, conditional probability, independent events, and sampling with/without replacement.
- OGM.12.STA.3Open Global Math Standards 2026™ · Math · Level 12 / High School 3 (Age 16) · Grade 11Design statistical experiments and random sampling methods; evaluate published statistical studies, media reports, and sample surveys; draw valid inferences and critique misleading statistical claims.
Curriculum Framework
11th Grade · Math · Open Global Math
1
9 lessons
Univariate Data: Center, Position, Dispersion, and Distributions
Analyze univariate quantitative data by calculating and interpreting measures of central tendency, position, dispersion, and evaluating frequency distributions.
2
7 lessons
Bivariate Association: Covariance and Correlation Analysis
Quantify, interpret, and evaluate bivariate numerical associations using scatter plots, sample covariance, and Pearson's correlation coefficient.
3
7 lessons
Combinatorics and Counting Techniques
Master counting principles, permutations, and combinations to quantify outcomes in complex multi-stage probabilistic systems.
4
7 lessons
Foundations of Probability, Sample Spaces, and Compound Events
Construct formal sample spaces and calculate probabilities for simple, complementary, mutually exclusive, and compound events.
5
7 lessons
Conditional Probability, Tree Diagrams, and Bayes' Theorem
Evaluate conditional probabilities, test for statistical independence, and compute revised probabilities using the Law of Total Probability and Bayes' Theorem.
6
7 lessons
Statistical Study Design and Random Sampling Methodologies
Design valid comparative experiments and representative random sampling protocols while mitigating bias and confounding variables.
7
7 lessons
Critiquing Media Claims, Statistical Fallacies, and Inferential Reasoning
Evaluate published reports, public opinion polling data, deceptive graphics, and common statistical fallacies to draw sound inferential conclusions.