This preview shows pages 1–2. Sign up to view the full content.
52 The Standard Normal Distribution
Objectives
: Students will be able to:
•
Calculate probabilities under the standard normal curve.
The ideas in this section serve as important groundwork for the remaining content in this
course.
Recall that a discrete probability distribution has the following properties:
1.
() 1
Px
=
∑
2.
01
x
≤≤
The
Normal Distributions
are
continuous
distributions under the curve
2
1
2
()
2
x
e
y
μ
σ
π
−
−
=
.
Definition
Requirements for a Continuous Distribution
A
density curve
(or
probability density function
(PDF) is a graph of a continuous
probability distribution that has the following properties:
1. The total area under the curve must equal 1; and
2. Each point on the curve must have a height of 0 or greater.
The
Standard Normal Distribution
is a normal probability distribution that has a mean
of 0 and a standard deviation of 1, and the area underneath the curve is 1.
Because the total area under the density curve is equal to 1, there is a
correspondence between
area
and
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
This is the end of the preview. Sign up
to
access the rest of the document.
 Spring '07
 Stone
 Statistics, Normal Distribution

Click to edit the document details