indicated probability formula

Cumulative frequency is obtained by adding the frequency of a class interval and the frequencies of the preceding intervals upto that class interval. This is explained by an example below. The following frequency distribution table gives the marks obtained by 40 students: Table (a) The frequencies ..

(i) The class intervals are made continuous and then the histogram is constructed. (ii) A kink or a zig - zag curve is shown near the origin. It indicates that the scale along the horizontal axis does not start at the origin. (iii) The horizontal scale and vertical scale need not..

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Introduction - In our day to day life, we come across many uncertainty of events. We wake up in the morning and check the weather report. The statement could be 'there is 60% chance of rain today'. This statement infers that the chance of rain is more than that having a dry weather. We decide upon ..

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..

If a trial results in n-exhaustive, mutually exclusive and equally likely cases and m of them are favourable to the occurrence of an event A, then the probability of the happening of A, denoted by P(A), is given by: P(A) = m/n. Important terms are 1. Statistical or Empirical P..

Probability of an Event - So far, we have introduced the sample of an experiment and used it to describe events. In this section, we introduce probabilities associated to the events. If a trial results in n-exhaustive, mutually exclusive and equally likely cases and m of them ar..

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..

Probability (continued)..

1. Addition Rule of Probability: If A and B are any two events, then 2. P(A C ) = 1 - P(A). 3. P( f ) = ..