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Lecture 6

# STAT 2507 Lecture Notes - Lecture 6: Exponential Distribution, Probability Distribution, Random VariablePremium

3 pages85 viewsWinter 2018

This

**preview**shows half of the first page. to view the full**3 pages of the document.**Chapter 6

The Normal Probability Distribution

Probability Distributions For Continuous Random Variables Examples: Heights Weights,

Length of life of a particular product Distance travelled on a trip Probability Density Function

A probability density function (f(x)) is a model for the probability distribution of a continuous

random variable X.

Probability Distributions For Continuous Random Variables Examples: Heights Weights,

Length of life of a particular product Distance travelled on a trip Probability Density Function

A probability density function (f(x)) is a model for the probability distribution of a continuous

random variable X.

Probability Density Function The probability density function has the following properties:

fx 0. The area under the probability density function equals 1. P(X=a)=0. In other words,

the probability at a specific point is equal to zero. PX a=PX > a and PX a=PX < a) as a

result from the previous point. (Remember that this is not true for discrete random

variables!!!!! Note: Pa < X < b = Pa X < b = Pa < X b = Pa X b .

Exercise 1

Uniform Distribution

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