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Suppose we randomly select a sample of 100 blue-collar workers, and suppose the sample mean mean of unpaid time lost during a three-month period actually exceeds 1.5 days. Would it be reasonable to conclude that the mean amount of unpaid time lost has increased above the previously estimated 1.0 days? Explain.
After performing a two sample t-test, you see a p-value of 0.0355. Of the following, which is the appropriate conclusion?
a) Explain why it would be hard to take a Simple Random Sample? b) Describe how to take a cluster sample of chocolate chip cookies.
At the .05 significance level, can we conclude that the guideline is still reasonable?
Standard deviation of 50. what is the probability that next year the number of burgalaries will be less than 250? less than 300 and more than 350?
A sports researcher gave a standard written test of eating habits to 12 randomly selected professionals, four each from baseball, football, and basketball. The results were as follows:
Use these statistics to construct a 94% confidence interval for the mean monthly consumption for the population of all Ontario households.
Using the spreadsheet for exercises 1-3, estimate how the population will change from this generation to the next under each of the following conditions.
Consider a hypothesis test that uses a 0.05 significance level to test the claim that the mean body tem of the population is less than 98.6
The following data represent the number of weed-eaters sold per month at a local garden shop and their prices
Using standard methods for linear statistical prediction, find the percent increase in sales revenue that would be expected if the price were lowered by 15%. Find the usual measure of the strength of association between price reduction and sales re..
Suppose the annual return on XYZ stock follows a normal distribution with mean 0.12 and standard deviation 0.30.
Although the phenomnenon is not well understood, it appears that people born during the winter months are slightly more likely to develop schizophrenia than people born at other times.
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