Qmb Chapter 6 Sampling Distributions

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Chapter 6 Sampling Distributions True/False 1. If we have a sample size of 100 and the estimate of the population proportion is .10, we can estimate the sampling distribution of [pic]with a normal distribution. Answer: True Difficulty: Easy 2. A sample size of 500 is sufficiently large enough to conclude that the sampling distribution of [pic] is a normal distribution, when the estimate of the population proportion is .995. Answer: False Difficulty: Medium 3. The sampling distribution of [pic] must be a normal distribution with a mean 0 and standard deviation 1. Answer: False Difficulty: Medium (REF) 4. For any sampled population, the population of all sample means is approximately normally distributed. Answer: False Difficulty: Medium 5. The sampling distribution of a sample statistic is the probability distribution of the population of all possible values of the sample statistic. Answer: True Difficulty: Easy 6. A sample statistic is an unbiased point estimate of a population parameter if the mean of the populations of all possible values of the sample statistic equals the population parameter. Answer: True Difficulty: Medium 7. A minimum variance, unbiased point estimate has a variance that is as small or smaller than the variances of any other unbiased point estimate. Answer: True Difficulty: Medium 8. We can randomly select a sample from an infinite population of potential process measurements by sampling the process at different and equally spaced time points. Answer: True Difficulty: Medium (REF) 9. The reason sample variance has a divisor of n-1 rather than n is that it makes the variance an unbiased estimate of the population variance. Answer: True Difficulty: Hard 10. The standard deviation of all possible sample proportions increases as the sample size increases. Answer: False