find the probability of independent events. if you toss a coin 3 times what is the probability that the coin will land showing h

In tossing of a coin, there are two exhaustive cases, {H}, {T}. In throwing of a dice, there are 6 exhaustive cases, {1}, {2}, {3}, {4}, {5}, {6}. In throwing of a pair of dice, there are 36 exhaustive cases. Example of an event which is ..

Each element of S denotes a possible outcome. Each element of S is known as sample point. Any trial results in an outcome and corresponds to one and only one element of the set S. e.g., 1. In the experiment of tossing a coin, S = {H, T} 2. In the experiment of h..

An event is the outcome or a combination of outcomes of an experiment. In other words, an event is a subset of the sample space. e.g., {a head} in the experiment of tossing a coin is an event. {a sum equal to 6} in the experiment of throwing a pair of di..

There can be several r.v's associated with an experiment. A random variable which can assume only a finite number of values or countably infinite values is called a discrete random variable. e.g., Consider a random experiment of tossing three coins simultaneously. Let X denote ..

Random Variables and Probability Distributions - It is often very important to allocate a numerical value to an outcome of a random experiment. For example, consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome HH HT TH TT No..

It is often very important to allocate a numerical value to an outcome of a random experiment. For example, consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome HH HT TH TT No. of heads (x) 2 1 1 0 x is called a random variable, which..

Conclusion - 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 bi..

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 distri..

So far, we have assumed that the elementary events are equally likely and we have used the corresponding definition of probability. However the same definition of conditional probability can also be used when the elementary events are not equally likely. Thi..

. Proceeding in this way, we see that there are n(n-1)(n-2)(n-3)(n-4)....[r factors] different ways of filling r blank spaces with n letters. The r t h factor = n - (r -1) = n - r = 1. The number of r-permutations of n different things is n P r = P(n,r) = n(n-1) (n-2) (n-3h..