Introduction to Quantitative Methods

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Pages : 395; Paperback;
210 X 275 mm approx.

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Pages : 276; Paperback;
210 X 275 mm approx, Sample Applied Theory Questions
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<< Chapter 10

Probability Distributions : Chapter 11

SUMMARY: Probability distributions are considered as theoretical frequency distributions. As these distributions deal with expectations, they are used in making inferences and decisions under uncertainty conditions.

Random variable is a variable that takes different values as a result of the outcomes of a random experiment. The expected value of a random variable is obtained by multiplying each value that the variable can assume with the probability of occurrence of that value and then summing up these products. This chapter discusses the concepts of random variables and their expected values.

Probability distributions can be broadly classified into two types: discrete and continuous. The binomial distribution describes discrete, non-continuous data resulting from an experiment. Poisson distribution applies to a situation when an event occurs at random points in

time or space. This chapter discussed the conditions that are to be met by a process so that it can follow a Poisson distribution. This chapter also discussed the concepts of hypergeometric distribution