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YOUR STUDY SPACE · CBSE

Probability — Class 12 Mathematics

Mathematics Part II · Chapter 7

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Chapter summary

This chapter develops probability beyond simple counting. Conditional probability measures the chance of given that has occurred. The multiplication theorem follows: . Two events are independent when . The Theorem of Total Probability sums the contributions of mutually exclusive, exhaustive events, and Bayes' Theorem reverses conditioning to find from the prior probabilities and likelihoods. A random variable assigns a number to each outcome; its probability distribution leads to the mean (expectation) and variance. The binomial distribution, modelling independent Bernoulli trials with success probability , gives .
Conditional probabilityMultiplication theorem and independenceTotal probability and Bayes' TheoremRandom variables and expectationBinomial distribution

Key ideas & terms

Conditional probability
, .
Independent events
Events with .
Total probability
Summing over exhaustive events.
Bayes' Theorem
Reverses conditioning to find .
Random variable
A function assigning a real number to each outcome.
Binomial distribution
.

Extra questions & answers

Define conditional probability.

, provided ; it is the probability of given that has occurred.

State the multiplication theorem of probability.

.

When are two events independent?

When ; equivalently .

State Bayes' Theorem.

, for mutually exclusive, exhaustive events .

State the Theorem of Total Probability.

For exhaustive, mutually exclusive events , .

Define a random variable.

A real-valued function defined on the sample space of a random experiment, assigning a number to each outcome.

Write the mean of a random variable .

, the expected value of .

State the binomial probability formula.

, , for independent trials with success probability .

Give the mean and variance of a binomial distribution.

Mean and variance .

What conditions define a binomial experiment?

A fixed number of independent trials, each with only two outcomes (success/failure) and a constant success probability .

Write the formula for the theoretical probability of an event E.

.

What is the probability of a sure event and of an impossible event?

for a sure (certain) event and for an impossible event.

What is the range of the probability of any event?

The probability of any event lies between 0 and 1, that is .

What are complementary events, and how are their probabilities related?

An event and "not " are complementary; , so .

A die is thrown once. What is the probability of getting an even number?

Favourable outcomes are 2, 4, 6 (three of them) out of six, so .

A card is drawn from a well-shuffled pack of 52. What is the probability that it is a king?

There are 4 kings, so .

Two coins are tossed together. What is the probability of getting two heads?

The outcomes are HH, HT, TH, TT; only one is favourable, so .

If the probability of an event is 0.7, what is the probability of its not happening?

.