Qmb Chapter 6 Sampling Distributions Essay

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   Difficulty: Medium   (REF)

11.   The central limit theorem states that as sample size increases, the...