Personnel Assignment Problem
If we are given the number of persons, number of jobs and the expected productivity of a particular person on a particular job, linear programming is used to maximise the average productivity of a perso..
Mean and Variance of a Discrete Random Variable
Let X be a discrete random variable which can assume values x 1 , x 2 , x 3 ,x n with probabilities p 1 , p 2 , p 3 .. p n respectively then (a) Mean of X or expectation of X denoted by E(X) or m is given by (b) Variance of X denoted by s 2 is given ..
Let X be a discrete random variable which can assume values x 1 , x 2 , x 3 ,x n with probabilities p 1 , p 2 , p 3 .. p n respectively then (a) Mean of X or expectation of X denoted by E(X) or m is given by (b) Variance of X denoted by s 2 is given ..Probability concepts and probability theorems
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 ..
Probability (continued)
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..
Probability of an Event
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
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..
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..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 the information, that the event B has occurred, then the 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 the information, that the event B has occurred, then the probability..Probability (continued)
Probability (continued)..
Probability (continued)..Theorems of Probability
1. Addition Rule of Probability: If A and B are any two events, then 2. P(A C ) = 1 - P(A). 3. P( f ) = ..
1. Addition Rule of Probability: If A and B are any two events, then 2. P(A C ) = 1 - P(A). 3. P( f ) = .. Result
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