Exam 7: Sampling and Sampling Distributions

In sampling,a population is:

Selecting a random sample from each identifiable subgroup within a population is called:

In stratified sampling,the population is divided into relatively homogeneous subsets called strata,and then random samples are taken from each stratum.

With proportional sample sizes:

If the sample size is greater than 30,the Central Limit Theorem (CLT)will always apply.

The difference between the point estimate and the true value of the population parameter being estimated is called the estimation error.

The defining property of a simple random sample is that:

Cluster sampling is often less convenient and more costly than other random sampling methods.

Which of the following is not a consideration when determining appropriate sample size?

The Central Limit Theorem (CLT)states that the sampling distribution of the mean is approximately normal,no matter what the distribution of the population,so long as the sample size is large enough.

Stratified samples are typically not used in real applications because they provide less accurate estimates of population parameters for a given sampling cost.

Identifiable subpopulations within a population are called:

Voluntary response bias occurs when the responses to questions do not reflect what the investigator had in mind.

A list of all members of the population from which we can choose a sample is called a frame,and the potential sample members are called sampling units.

We can measure the accuracy of judgmental samples by applying some simple rules of probability.This way,judgmental samples are not likely to contain our built-in biases.

A sampling error is the result of:

In stratified sampling with proportional sample sizes,the proportion of each stratum selected differs from stratum to stratum.