Exam 7: Sampling and Sampling Distributions

The accuracy of the point estimate is measured by its:

There is approximately % chance that any particular $\bar { X }$ Will be within two standard deviations of the population mean ( $\mu$ ))

The opportunity for sampling error is decreased by:

The averaging effect says that as you average more and more observations from a given distribution,the variance of the average increases.

The sampling distribution of any point estimate (such as the sample mean or proportion)is the distribution of the point estimates we would obtain from all possible samples of a given size drawn from the population.

The sampling distribution of the mean will have the same mean as the original population from which the samples were drawn.

The sampling distribution of the mean will have the same standard deviation as the original population from which the samples were drawn.

A judgmental sample is a sample in which the

Which of the following statements are correct?

A confidence interval is an interval calculated from the population data,where we strongly believe the true value of the population parameter lies.

The Central Limit Theorem (CLT)is generally valid for:

In systematic sampling,one of the first k members is selected randomly,and then every k^th member after this one is selected.The value k is called the sampling interval and equals the ratio N / n,where N is the population size and n is the desired sample size.

Non-truthful response is a particular problem when:

In cluster sampling,the population is divided into subsets called clusters (such as cities or city blocks),and then a random sample of the clusters is selected.Once the clusters are selected,we typically sample all of the members in each selected cluster.

Systematic sampling is generally similar to simple random sampling in its statistical properties.

The finite population correction factor, $\sqrt { \frac { N - n } { N - 1 } }$ ,should generally be used when:

If a simple random sample of size n is chosen from a population of size N,then each member of the population has probability N / n of being chosen in the sample.

The mean of the sampling distribution of $\bar { X }$ Always equals

An unbiased estimator is a:

The primary advantage of cluster sampling is sampling convenience (and possibly less cost).The downside,however,is that the inferences drawn from a cluster sample can be less accurate,for a given sample size,than for other sampling plans.