More on Normal Distributions

First, this section talks about the history of the normal distribution and the central limit theorem and the relation of normal distributions to errors. Then, it discusses how to compute the area under the normal curve. It then moves on to the normal distribution, the area under the standard normal curve, and how to translate from non-standard normal to standard normal. Finally, it addresses how to compute (cumulative) binomial probabilities using normal approximations.

Question 1 out of 6.
A distribution has a mean of 40 and a standard deviation of 5. 68% of the distribution can be found between what two numbers?

 30 and 50

 0 and 45

 0 and 68

 35 and 45

Question 2 out of 6.
A distribution has a mean of 20 and a standard deviation of 3. Approximately 95% of the distribution can be found between what two numbers?

 17 and 23

 14 and 26

 10 and 30

 0 and 23

Question 3 out of 6.

A normal distribution has a mean of 5 and a standard deviation of 2. What proportion of the distribution is above 3?

Question 4 out of 6.

A normal distribution has a mean of 120 and a variance of 100. 35% of the area is below what number?

Question 5 out of 6.

A normal distribution of test scores has a mean of 38 and a standard deviation of 6. Everyone scoring at or above the 80th percentile gets placed in an advanced class. What is the cutoff score to get into the class?

Question 6 out of 6.

A normal distribution of test scores has a mean of 38 and a standard deviation of 6. What percent of the students scored between 30 and 45?