what is the probability of selecting a head when a coin is tossed if the probability of selecting a tail is 12?

B) is the event of the occurrence of both events A and B. If A and B happen to be mutually exclusive events, then P(A B) = 0. For example, in the experiment of tossing three coins, if A and B be the events of getting at least one head and at most one tail res..

Random Variable and Probability Distribution - If 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..

If 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..

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..

Events - 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 dice is ..

Let S is the sample space which is the population of adults in a small town who have completed the requirement for a college degree. The population is categorized according to sex and employment status as follows \ One of these individual is to be selected for a tour throughout the c..

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 exhaustive, but not mutually e..

Let X be the random variable which represents number of defective items selected which has a binomial distribution with n = 10, p = 0.1, q = 0.9 Probability that the guarantee is satisfied = ..

is the mid-point of each interval. Class mark for Class (11 - 15) is . Similarly, class marks for other intervals are 18, 23, 28 When the data is put in a frequency distribution table, the marks obtained by an individual has lost its meaning. Thus some details have been lost. But we have learn..

The selection of a number of things taking some or all of them at a time are called combinations. The number of ways of selecting r things out of n dissimilar things is denoted by C(n, r) or n C ..