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1. Explain in your own words the law of large numbers. Provide an example to illustrate.
2. Explain in your own words, using the definition of probability why: a) the probability of an event that cannot occur is 0; b) the probability of an event that must occur is 1.
3. Why is expectation important? Explain what the expected value of an experiment or a business represents. What does it mean to have an expected value of 0? Provide an example of expectation and the use of the formula for expected value.
4. What are the reasons for studying statistics?
5. From your readings, select a sampling technique of your choice. Describe how the technique can be used to obtain the type of sample. Indicate when the technique may be preferred. List two examples of when the sampling technique may be used.
Find an equation of the least squares regression line. Please show your work. Is there a linear correlation between "x" and "y" at the 0.01 significance level? Please justify your answer.
Provide an example of three events that would be mutually exclusive. Are these events also exhaustive? Then, give an example of three events that would be exhaustive. Are these exhaustive events also mutually exclusive?
If a member of this senior class is selected at random, find the probability that the student a) smokes but does not drink alcoholic beverages; b) eats between meals and drinks alcoholic beverages but does not smoke; c) neither smokes nor eats bet..
Your mayor just announced that the local unemployment rate dropped last month from the prior month. It went from 10.5% to 10.4%. Is this a significant drop? Explain.
Shall we reject the hypothesis that the population mean is 6.0? Interpret the result.
Suppose it has been determined that the average number of customers waiting for service is 1.929. There are two servers. Determine:
When such digits are randomly generated, what is the distribution of those digits? Given such randomly generated digits, what is a test for "goodness-of-fit"?
Either no change to the Objective function or a raise in the value of the objective function depends on the constraint.
At the .05 significance level, is the number of units produced on the afternoon shift larger?
Get an answer from tutors to this homework question now: Under what circumstances is the experimentwise alpha level a concern?
The MacBurger restaurant chain claims that the waiting time of customers for service is normally distributed, with a mean of 3 minutes and a standard deviation of 1 minute.
Given the binomial distribution with n = 23 and p = 0.79, would the normal distribution provide the reasonable approximation? Why or why not?
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