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ABC Auto Insurance classifies drivers as good, medium, or poor risks. Drivers who apply to them for insurance fall into these three groups in the proportions: 30 percent, 50 percent, and 20 percent, respectively. The probability a "good" driver will have an accident is .01, the probability a "medium" risk driver will have an accident is .03, and the probability a "poor" driver will have an accident is .10. The company sells Mr. Brophy an insurance policy and he has an accident. What is the probability Mr. Brophy is :
Frequently, tests tha yeild abnormal results are repeated for confirmation. What is the probability that for a normal person a test will be at least 1.5 times as high as the upper limit of normal on two seperate occasions.
Construct a 99% confidence interval estimate of the population mean amount of paint in a 1-gallon can.
A random sample of n = 16 scores is selected from a normal distribution with a mean of μ = 50 and standard deviation of σ = 10. a) What is the probability that the sample mean will have a value between 45 and 55?
Critically discuss the difference among strategic, long-term, and short-term objectives? What is the relationship between objectives and goals? What are examples of this relationship?
Generate descriptive statistics. Create a stem-and-leaf plot of the data and box plot of the data.
According to the data from the College Entrance Examination Board, scores on the SAT-I test have a mean of 1017, and Q1 is 880.
If we assume that the lifetime of this type of bulb has a standard deviation of 400 hours, can we conclude at the 5% significance level that the claim is true.
The times needed to fall asleep are assumed to follow a normal distribution. The results for the two nights for the ten volunteers are shown below:
Illustrate a quantitative assessment of what our charts would look like and what these new targets would do to our operations.
Find the value of x that corresponds to each of these standard scores z = -1.85.
Discuss how the null and alternative hypothesis for one-sample testing differs from two-sample testing; and explain how these two hypothesis' are the same, and provide a numerical example?
In looking at your business, when and why would you want to use a one-sample mean test (either z or t) or a two-sample t-test? Create a null and alternate hypothesis for one of these issues. How would you use the results?
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