Probability
Madhya Pradesh Board · Class 12 · Mathematics
Summary of Probability for Madhya Pradesh Board Class 12 Mathematics. Key concepts, important points, and chapter overview.
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Probability measures uncertainty in a random experiment and is treated as a function of outcomes in the axiomatic approach of A.N. Kolmogorov. The chapter develops conditional probability, multiplication rules, independence, partitions of a sample space, the theorem of total probability, Bayes' theo
Key Concepts
The probability of event E given
The probability of event E given that event F has already occurred is P(E|F)=P(E∩F)/P(F), provided P(F)≠0. It means the sample space is restricted to
For any event F with P(F)≠0
For any event F with P(F)≠0, P(S|F)=1, P(E'|F)=1-P(E|F), and P((A∪B)|F)=P(A|F)+P(B|F)-P((A∩B)|F). If A and B are disjoint, then P((A∪B)|F)=P(A|F)+P(B|
For two events
For two events, P(E∩F)=P(E)·P(F|E)=P(F)·P(E|F), provided P(E)≠0 and P(F)≠0. For three events, P(E∩F∩G)=P(E)P(F|E)P(G|EF).
Two events E and F
Two events E and F are independent if P(F|E)=P(F) and P(E|F)=P(E), and equivalently if P(E∩F)=P(E)·P(F). Independent events with nonzero probability c
Three events
Three events A, B, and C are mutually independent if all pairwise products and the triple product hold: P(A∩B)=P(A)P(B), P(A∩C)=P(A)P(C), P(B∩C)=P(B)P
Learning Objectives
- Understand conditional probability and compute it using P(E|F)=P(E∩F)/P(F), P(F)≠0
- Apply properties of conditional probability, including union and complement rules
- Use the multiplication rule for two and three events
- Identify independent and dependent events and distinguish independence from mutual exclusiveness
- Recognize mutual independence of three events
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