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Tanima Dutta, Lovely Professional University Unit 13: Binomial Probability Distribution

Unit 13: Binomial Probability Distribution Notes

CONTENTS
Objectives
Introduction
13.1 Concept of Probablity Distribution
13.1.1 Probability Distribution of a Random Variable

13.1.2 Discrete and Continuous Probability Distributions
13.2 The Binomial Probability Distribution
13.2.1 Probability Function or Probability Mass Function
13.2.2 Summary Measures of Binomial Distribution
13.3 Fitting of Binomial Distribution
13.3.1 Features of Binomial Distribution
13.3.2 Uses of Binomial Distribution

13.4 Summary
13.5 Keywords
13.6 Review Questions
13.7 Further Readings

Objectives

After studying this unit, you will be able to:
Brief about theoretical probability distribution

Categorize theoretical probability distribution
Define the term binomial probability distribution
Explain the various features of binomial probability distribution
Discuss the uses and measures of binomial probability distribution

Introduction

The study of a population can be done either by constructing an observed (or empirical) frequency
distribution, often based on a sample from it, or by using a theoretical distribution. We have
already studied the construction of an observed frequency distribution and its various summary
measures. Now we shall learn a more scientific way to study a population through the use of
theoretical probability distribution of a random variable. It may be mentioned that a theoretical
probability distribution gives us a law according to which different values of the random
variable are distributed with specified probabilities. It is possible to formulate such laws either
on the basis of given conditions (a priori considerations) or on the basis of the results (a posteriori
inferences) of an experiment.
If a random variable satisfies the conditions of a theoretical probability distribution, then this
distribution can be fitted to the observed data.

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