The central limit theorem proposes that:       The distribution of sample means will be approximately normal in shape only if the underlying population distribution is normal and provided that sample sizes are large enough (i.e., N = 30 or greater)       The distribution of sample means will be approximately normal in shape only if the original sample distribution was normal       The mean of any given sample will approximately equal the population mean       The distribution of sample means will be approximately normal regardless of the original sample distribution shape, provided sample sizes are large enough (i.e., N = 30 or greater)

Inferential statistical analyses that are not based on a set of assumptions of the z test? a. Permissible only when certain assumptions about the sample are met b. nonparametric c. parametric d. innacurate

Executives of a supermarket chain are interested in the amount of time that customers spend in the stores during shopping trips. The executives hire a statistical consultant and ask her to determine the mean shopping time, μ, of customers at the supermarkets. The consultant will collect a random sample of shopping times at the supermarkets and use the mean of these shopping times to estimate μ. Assuming that the standard deviation of the population of shopping times at the supermarkets is 27 minutes, what is the minimum sample size she must collect in order for her to be 95% confident that her estimate is within 5 minutes of μ? Carry your intermediate computations to at least three decimal places. Write your answer as a whole number (and make sure that it is the minimum whole number that satisfies the requirements).

An estimator that tends to produce more accurate estimates of the population parameter as the sample size increases is best characterized as a(n)_____________Select one: A. A consistent estimator approaches the estimated population parameter as the sample size grows larger. B. An unbiased estimator is consistent if its standard error is lower than that of other estimators of the estimated population parameter. C. An estimator is consistent if its expected value equals the estimated population parameter. D. An estimator is consistent if it always gives the correct value of the estimated population parameter.

A random sample of size 10 yielded roughly "mound-shaped" data with a sample mean of 63.5 and a sample variance of 60.8. Let (L, OU) be the interval estimate that contains the population mean with 95% probability. Find the width of the interval. That is, find 0 – 0₁. 4.52 5.49 5.58 5.70 9.04 10.99 11.16 11.40 none of the other answers give the correct width