Exam 7: Sampling and Sampling Distributions

Auditors of Old Kent Bank are interested in comparing the reported value of customer savings account balances with their own findings regarding the actual value of such assets. Rather than reviewing the records of each savings account at the bank, the auditors decide to examine a representative sample of savings account balances. The frame from which they will sample is shown below. -A cannery claims that its sardine cans have a net weight of 8 oz., with a standard deviation of 0.1 oz. You take a simple random sample of 30 cans and encounter a sample mean of 7.85 oz. Are you inclined to believe the claim?

A point estimate is a single numeric value, a "best guess" of a population parameter, calculated from the sample data.

The sampling method in which a population is divided into blocks and then selected by choosing a random mechanism is called a:

The opportunity for sampling error is decreased by:

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

There is an approximately _____% chance that any particular will be within two standard deviations of the population mean ( ).

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

Sampling error is evident when:

The central limit theorem (CLT) states that the sampling distribution of the mean is approximately normal, no matter what the distribution of the population, as long as the sample size is large enough.

Potential sample members, called sampling units, are:

The randomized response technique is a way of getting at sensitive information to avoid estimation errors due to nontruthful responses.

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

A sample in which the sampling units are chosen from the population by means of a random mechanism is a:

The central limit theorem (CLT) says that as long as the sample size is reasonably large, there is about a 95% chance that the magnitude of the sampling error for the mean will be no more than two standard errors.

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

The central limit theorem (CLT) is considered to be an important result in statistics because:

The approximate standard error of the sample mean is calculated as:

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.

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

The accuracy of the point estimate is measured by its: