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An internal study by the Technology Services department at Lahey Electronics revealed company employees receive an average of 6.0 emails per hour. Assume the arrival of these emails is approximated by the Poisson distribution.
(a) What is the probability Linda Lahey, company president, received exactly 3 emails between 4 P.M. and 5 P.M. yesterday? (Round your answer to 4 decimal places.)
(b) What is the probability she received 7 or more emails during the same period? (Round your answer to 4 decimal places.)
(c) What is the probability she did not receive any emails during the period? (Round your answer to 4 decimal places.)
Two tools that are often used in this process are the contingency table and the decision tree. What are these tools and how to they help us to make decisions under uncertainty when we are dealing with probabilities?
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A study was conducted with 35 people that resulted in a mean of 22.1 minutes with a standard deviation of 1.9 minutes. Using a .05 significance level, test the claim that the mean amount of time relief will be felt is less than 25 minutes.
What type of situation would I be able to understand how to use regression as a key driver as an influence in sales or other outcomes?
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We want to test the hypothesis that the population variances are equal.
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Based on the result, does there to be an overall perception of 1 minute that is reasonably accurate?
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