(Ch 8.2) True or False? In any random sample drawn from a population, the sample mean is an unbiased estimator of the population mean.
11. (Ch 8.2) A consistent estimator for the population mean a. collapses on the true parameter μ as the variance increases. b. collapses on the true parameter μ as the sample size increases. c. consistently follows a normal distribution. d. is impossible to obtain using real sample data.
12. (Ch 8.3) The Central Limit Theorem (CLT) implies that a. the population will be approximately normal if the sample size n is at least 40. b. repeated samples must be taken to obtain normality. c. the distribution of the sample mean is approximately normal for a large n. d. the sample mean is not an unbiased estimator of the population mean.
13. (Ch 8.3) True or False? The Central Limit Theorem says that, if the sample size n exceeds 30, then it must be the case that the population will be normal.
14. (Ch 8.4) True or False? A higher confidence level leads to a narrower confidence interval.
T
B
C
F
F