Continuous Random Variables
Completion requirements
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. \(64\)