# Qmb Chapter 6 Sampling Distributions Essay

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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.

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.

3.   The sampling distribution of [pic] must be a normal distribution with a mean 0 and standard deviation 1.

4.   For any sampled population, the population of all sample means is approximately normally distributed.

5.   The sampling distribution of a sample statistic is the probability distribution of the population of all possible values of the sample statistic.

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.

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.

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.

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.

10.   The standard deviation of all possible sample proportions increases as the sample size increases.

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

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