Paper II · 3 Probability · 3.2 Probability and probability distributions
3.2.1 Conditional probability, independent events, total probability and Bayes' theorem
Conditional probability P(B | A) is the chance of B after we know A has happened; events are independent when this knowledge changes nothing, the total probability theorem adds up the routes to an event, and Bayes' theorem turns the question around to find which route was taken.
- TGPSC MPSO / ASO · Paper II
- Advanced level
- 8 min read
- Full course
Key terms
- conditional probability
- multiplication theorem
- independent events
- pairwise independence
- mutual independence
- dependent events
- partition
- theorem of total probability
- Bayes theorem
- prior probability
- posterior probability
- likelihood
- inverse probability
What this note covers
- Core factsFoundation
- ExplainedStandard
- DeeperAdvanced
- Common trapsFoundation
- Quick revisionFoundation
Read the full note in the app. It is part of the TGPSC MPSO / ASO full course in Medha AI. Free in the app: the first chapter of each topic.
All Probability and probability distributions notes · TGPSC MPSO / ASO syllabus · TGPSC ASO Paper I Mock 1 with answers · Start free
Medha AI writes its own notes and checks them against the sources listed. Medha AI is an independent preparation service. It is not affiliated with, endorsed by or connected to APPSC, TGPSC (formerly TSPSC), MPSC, UPSC or any other commission or government body.