Suppose that the distribution of retirement age in Canada is negatively skewed. The distribution has a mean of 65 and a variance of 16. (a) For a random sample of n = 81 retired Canadians, what is the probability that the average age of retirement in the sample is less than 64.5? (b) For a random sample of n = 81 retired Canadians, what is the probability that the average age of retirement in the sample is between 65 and 66? (c) At what age would have at least 90% of the individuals in the sample retired? In other words, what is the 90th percentile for a random sample of n = 81 retired Canadians?
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Suppose that the distribution of retirement age in Canada is negatively skewed. The distribution has a mean of 65 and a variance of 16.
(a) For a random sample of n = 81 retired Canadians, what is the
(b) For a random sample of n = 81 retired Canadians, what is the probability that the average age of retirement in the sample is between 65 and 66?
(c) At what age would have at least 90% of the individuals in the sample retired? In other words, what is the 90th percentile for a random sample of n = 81 retired Canadians?
(d) Everything else being equal, how would an increase in
(e) Everything else being equal, how would an increase in sample size influence σ?
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