Question

If you calculate a Z score of -2.26 the probability of getting a value less than that is: .0119 .9881 .0139 .0047 Question 2 If you calculate a Z score of +2.59 , the probability of getting a value greater than that is: .0048 .9952 .9938 .9981 If you calculate a Z score of -1.23 , the probability of getting a value greater than that is: .8907 .1093 .1587 .8413 Question 4 If you calculate a Z score of +1.28 , the probability of getting a score less than that is: .8997 .1003 .9245 1.8997 If you calculate a Z score of 32 , the probability of getting a score less than that is: .32 .68 .6255 .3745 Remember Really Big Medical Center (RBMC) from the last chapter? They are testing patients for Lyme disease. Suppose that in that study you calculated a mean of 5 and a standard deviation of .7 and you want to answer the following questions. The Z score for 7 people testing positive would be: At that Z-score, we would expect that percent of the time we would see more than 7 people with Lyme disease. According to the Empirical Rule, we would expectthat 95% of the time the number of patients with Lyme disease would be between: Using the Z curve we would expect that 95% of the time the number of patients with Lyme disease would be between: Benny is raising bat for Halloween this year. He has 50 mommy bats, and computes that their average litter size is 4.6 bats with a standard deviation of 1.4 bats. What is the probability of a litter of 3 or fewer baby bats? Suppose that the actual distribution of the number of bats in each litter and the number of moms who had that litter size is as follows: Using the exact (discrete) distribution, what is the probability of 3 or fewer bats in a litter?

Answer 1

The Z-score is a measure of how many standard deviations an individual data point is away from the mean. Probability can be calculated using Z-scores and the area under the normal curve. The Empirical Rule can be used to estimate the range of values within a certain number of standard deviations.

Step-by-step explanation:

The Z-score is a measure of how many standard deviations an individual data point is away from the mean of a distribution. To calculate the probability of getting a value less than a given Z-score, you can look up the area under the normal curve to the left of that Z-score in a Z-table. For example, a Z-score of -2.26 corresponds to a probability of 0.0119.

The probability of getting a value greater than a given Z-score can be calculated by subtracting the probability of getting a value less than that Z-score from 1. For example, a Z-score of +2.59 corresponds to a probability of 1 - 0.9952 = 0.0048.

Based on the mean and standard deviation provided, you can calculate the Z-score for the number of people testing positive for Lyme disease and use it to determine the expected percentage of the time you would see more than 7 people with Lyme disease. You can also use the Empirical Rule to estimate the range of the number of patients with Lyme disease that you would expect 95% of the time.