Free Sampling and Sampling Distributions MCQs with Answers

• A. Approximately normal because the sample size is small relative to the population size
• B. Approximately normal because of the central limit theorem
• C. Exactly
• D. None of these alternatives is correct

Explanation: With a sample size of only 17, the central limit theorem alone cannot ensure an approximately normal sample-mean distribution, because no…

• A. Bias
• B. Standard
• C. Sampling error
• D. both (a) and (b)

Explanation: Sampling error is the difference between a sample statistic and the corresponding population parameter.

• A. Serious error
• B. Dispersion
• C. Standard error
• D. Difference

Explanation: The standard deviation of a statistic's sampling distribution is called its standard error.

• A. Unknown
• B. Large
• C. Small
• D. Know

Explanation: In probability sampling, every sampling unit has a known, nonzero probability of selection.

• A. Four
• B. Six
• C. Three
• D. Seven

Explanation: The four commonly taught probability sampling methods are simple random, stratified, systematic, and cluster sampling.

• A. Sampling frame
• B. Sampling units
• C. Sample pop
• D. Sample design

Explanation: A sampling unit is the smallest identifiable member or group of members selected in a sample, such as a person, household, or institution.

• A. Only Once
• B. More than once
• C. Less than once
• D. None of these

Explanation: In sampling without replacement, a selected unit is removed from further consideration, so it cannot be selected again.

• A. Only when the sample size is at least 100.
• B. Only when the sample size is smaller than 30
• C. Always
• D. Only when the sample size is at least 30.

Explanation: A sample mean from a normally distributed population is normally distributed for every sample size.

• A. A portion of the sample
• B. A portion of the population
• C. all the items under investigation
• D. none of the above

Explanation: A sample is a selected portion of the population used to obtain information about the whole.

• A. Population
• B. Sample
• C. Data
• D. Observations

Explanation: A statistic is a numerical measure computed from a sample, whereas a numerical measure computed from a population is called a parameter.

• A. A sample
• B. A Parameter
• C. A Population
• D. Both b and c

Explanation: When information is collected from only a portion of the elements of interest, that portion is called a sample.

• A. Samples
• B. Primary
• C. Two
• D. Complete study

Explanation: Modern statistics commonly uses sample information to draw conclusions about a larger population, which is the basis of statistical…