conditional probability example help

Let A and B be any two events associated with a random experiment. The probability of occurrence of event A when the event B has already occurred is called the conditional probability of A when B is given and is denoted as P(A/B..

Let us consider the random experiment of throwing a die. Let A be the event of getting an odd number on the die. \ S = {1, 2, 3, 4, 5, 6} and A = {1, 3, 5} Let B = {2, 3, 4, 5, 6}. If, after the die is thrown, we are given the information, that the event B has occurred, then the probability..

Let A and B be any two events associated with a random experiment. The probability of occurrence of event A when the event B has already occurred is called the conditional probability of A when B is given and is denoted as P(A/B..

Introduction - From our earlier chapter we know that, in statistical experiments, if the events A and B are independent, then But suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by condit..

We have already proved that if two events A and B from a sample S of a random experiment are mutually exclusive, then In this section, we examine whether such a rule exists, if ' ' is replaced by ' ' and '+' is replaced by 'x' in the above addition rule. If it does exist, what are the particular ..

Multiplication Rule of Probability - We have already proved that if two events A and B from a sample S of a random experiment are mutually exclusive, then In this section, we examine whether such a rule exists, if ' ' is replaced by ' ' and '+' is replaced by 'x' in the above addition rul..

A set of values of the variables x 1 , x 2 , x 3 ,.,x n which satisfy all the constraints and also the non-negativity conditions is called the feasible solution of the LP..

Introduction - Suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by conditional probability. Baye's theorem is named after the British mathematician Thomas Bayes who publishe..

In this chapter we have studied the method of evaluating probabilities of events relating to independent events and conditional events. We have also studied about random variables and their probability distributions, namely binomial distribution and Poisson..

(a). Linear programming is applicable only to problems where the constraints and objective function are linear i.e., where they can be expressed as equations which represent straight lines. In real life situations, when constraints or objective functions are not linear, this technique cannot ..