Continuous Random Variables

First, this section talks about how to describe continuous distributions and compute related probabilities, including some basic facts about the normal distribution. Then, it covers how to compute probabilities related to any normal random variable and gives examples of using z-score transformations. Finally, it defines tail probabilities and illustrates how to find them.

Continuous Random Variables

Answers

1. The graph is a horizontal line with height 1 / 7 from x=5 to x=12

3. The graph is a bell-shaped curve centered at 100 and extending from about 70 to 130.

5. 0.212

7. 0.76

9. \mu_{A}=100, \mu_{B}=200, \mu_{C}=300, \sigma_{A}=7, \sigma_{B}=20, \sigma_{C}=15

11. 0.3542

13. a. The graph is a bell-shaped curve centered at 64 and extending from about 63.25 to 64.75.
b. 0.5
c. 64