1. Chapter 7 The Normal Distribution and Its Applications
7.1 Standard normal distribution N(0,1)
7.2 Transform to
7.3 The Normal Distribution

2. 7.1 Standard normal distribution N(0,1)
, for
Example
Refer to p.414 Standard normal curve
Given the standard normal variable Z ~ N(0,1), find the following probabilities:

3. Example2)
Given the standard normal variable Z ~ N(0,1), find the following probabilities:

4. Example Refer to p.414 Standard normal curve
Given the standard normal variable Z ~ N(0,1), find the following probabilities:

5. 7.2 Transform to

6. 7.3 The Normal Distribution
The normal distribution is the most important continuous distribution in statistics. Many measured quantities in the natural sciences follow a normal distribution, for example heights, masses, ages, random errors, I.Q. scores, examination results.
7.3.1 The Probability Density Function
 and 2 are the parameters of the distribution.
If X is distributed in this way we write
A continuous random variable X having p.d.f f(x) where
-  < x < 
is said to have a normal distribution with mean  and variance 2.
X  N(, 2).

7. Application of Normal Distribution
C.W.
Application of Normal Distribution
1)If the time a student stays in a classroom follows the normal distribution with and , what is the probability that he stays in a classroom for less than 5 hours?