Here again is the probability distribution of Y, the number of defective parts in an hour in Yves' production line: 1 2 P(Y = y) .05 .05 .10 .75 .05 Y 4 What is the expected number of defective parts in an hour? 2 .2 O 2.7 .54

Answer D

Here again is the probability distribution of Y, the number of defective parts in an hour in Yves' production line: Y 4 P(Y = y) .05 .05 .10 .75 .05 What is the expected number of defective parts in an hour? 02 0.2 O 2.7 0.54 Check Answer Type here to search

Suppose the time it takes for guests to wait for an elevator at the lobby of a certain office building has a uniform distribution between 0 and 4 minutes. What is the probability that, the next time you need to take this elevator, you'll have to wait at most 1.6 minutes? (Your answer should be a decimal. Round to 4 decimal places if necessary.)

Benford's Law claims that numbers chosen from very large data files tend to have "1" as the first nonzero digit disproportionately often. In fact, research has shown that if you randomly draw a number from a very large data file, the probability of getting a number with "1" as the leading digit is about 0.301. Suppose you are an auditor for a very large corporation. The revenue report involves millions of numbers in a large computer file. Let us say you took a random sample of n = 250 numerical entries from the file and r = 60 of the entries had a first nonzero digit of 1. Let p represent the population proportion of all numbers in the corporate file that have a first nonzero digit of 1. Test the claim that p is less than 0.301 by using α = 0.01. What does the area of the sampling distribution corresponding to your P-value look like?         a. The area in the right tail of the standard normal curve.   b. The area not including the right tail of the standard normal curve.…