Outline of Chapter 5 text - Elementary Statistics: A Brief Version(A. Bluman 3rd Ed., 2003)

Chapter 5 Outline

Objectives

Construct a hazard diffusion for a haphazard variable.

Find the mean, variance, and expected value for a discrete random variable.

Find the select probability for X successes in n trials of a binominal experiment.

Objectives (contd.)

Find the mean, variance, and standard difference for the variable of a binomial distribution.

Find probabilities for outcomes of variables using the Poisson, hypergeometric, and multinomial distributions.

Introduction

Many decisions in business, insurance, and other real-life situations ar made by assigning probabilities to all possible outcomes pertaining to the situation and then evaluating the results.

Introduction (contd.)

This chapter explains the concepts and applications of probability distributions. In addition, special probability distributions, much(prenominal) as the binomial, multinomial, Poisson, and hypergeometric distributions ar explained.

Random Variables

A random variable is a variable whose values are determined by chance.

Discrete Probability Distribution

A discrete probability distribution consists of the values a random variable can swallow and the corresponding probabilities of the values. The probabilities are determined theoretically or by observation.

Calculating the Mean

In order to find the mean for a probability distribution, unitary must multiply each possible outcome by its corresponding probability and find the sum of the products.

Rounding Rule

The mean, variance, and standard deviation should be rounded to one more decimal taper than the outcome, X.

Variance of a Probability Distribution

The variance of a probability distribution is found by multiplying the square of each outcome by its corresponding probability, summing those products, and subtracting the square of the mean.

The chemical formula for calculating the variance is:

The formula for the standard deviation is:

Expected Value

Expected value or expectation is apply in various types of games of chance, in insurance, and in other areas, such as decision theory.

Expected Value (contd.)

The expected value of a discrete...

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