conditional probability three

Conditional Probability - 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 ..

We have the following conditions on the variables x and y. a) Sum of the numbers is atleast 15 i.e., x + y 15 b) Difference of the numbers is at most 7 i.e., x - y 7 c) Since the x and y should be positive, we have two more conditions x > 0, y > 0 We call Z as objectiv..

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 distributio..

Poisson distribution is a limiting process of binomial distribution. Poisson distribution occurs when there are events which do not occur as outcomes of a definite number of outcomes. Poisson distribution is used under the following conditions: 1. Number of trials n tend..

Suppose we throw a die. Let E be the event of a perfect square number. Then E = {1,4}. Suppose 3 appeared on the upper most face, then we say that the event E has not occurred. E occurs only when 1 or 4 appears on the upper most face. Therefore whenever an outcome satisfies the cond..

So far we have learnt how to construct a mathematical model for a linear programming problem. If we can find the values of the decision variables x 1 , x 2 , x 3 , ..... x n , which can optimise (maximize or minimize) the objective function Z, then we say that these values of x i are the ..

There are mainly four steps in the mathematical formulation of linear programming problem as a mathematical model. We will discuss formulation of those problems which involve only two variables. 1. Identify the decision variables and assign symbols x and y to them. These decision variab..

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 LPP. Optimal Solution: The feasible solution, which optimises (i.e., maximizes or minimizes as the case may be) the objective function i..

Although the probability distribution of a continuous random variable cannot be presented in tabular form, it can have a formula in the form of a function represented by f(x) usually called the probability density functio..

Question: The median of the first ten prime numbers. Answer: The first 10 prime numbers ={2, 3, 5, 7, 11, 13, 17, 19, 23, 29} ..