Question 1

Which of the following best describes a census in statistics?

Accepted Answer

A collection of data from every member of the population.

Question 2

A researcher wants to estimate the average height of all students at a university. Which of the following would most likely be a representative sample?

Accepted Answer

Students in a statistics class open to all majors.

Question 3

Which of the following is an example of bias in a statistical study?

Accepted Answer

Reporting only the results that support the researcher's hypothesis.

Question 4

A supermarket offers free taste tests of a new salsa each morning. What type of sampling is this, and is it likely to be representative?

Accepted Answer

Convenience sampling; no, it is not likely to be representative.

Question 5

Which sampling method involves dividing the population into subgroups and then randomly sampling within each subgroup?

Accepted Answer

Stratified sampling

Question 6

Suppose you want to test the quality of microchips by selecting every 50th chip off the assembly line. What sampling method are you using?

Accepted Answer

Systematic sampling

Question 7

A researcher interviews 50 randomly selected athletes and 50 randomly selected nonathletes at a college. What sampling method is this?

Accepted Answer

Stratified sampling

Question 8

Which of the following statements about bias is TRUE?

Accepted Answer

Bias refers to any problem in the design or conduct of a study that tends to favor certain results.

Question 9

A company wants to estimate the percentage of farmers using organic techniques. They randomly select several counties and survey every farmer in those counties. What sampling method is this?

Accepted Answer

Cluster sampling

Question 10

Which of the following is a key requirement for a sample to be considered representative?

Accepted Answer

The sample must be chosen so that its relevant characteristics are generally the same as those of the population.

Question 11

A survey is conducted by selecting every 10th room in a co-ed dorm where odd rooms are male and even rooms are female. What is a likely problem with this sampling method?

Accepted Answer

It may result in a sample of only males or only females, making it unrepresentative.

Question 12

Which of the following best describes a simple random sample?

Accepted Answer

A sample in which every possible sample of a particular size has an equal chance of being selected.

Question 13

A study on unemployment divides the country into geographic regions and randomly selects households within each region. What is the main advantage of this approach?

Accepted Answer

It ensures that all regions are equally represented, accounting for regional differences.

Question 14

Which of the following is NOT a common sampling method discussed in the study materials?

Accepted Answer

Double-blind sampling

Question 15

A researcher uses a random number generator to select 100 students from a university roster. What type of sampling is this?

Accepted Answer

Simple random sampling

Question 16

Which of the following scenarios is most likely to result in a biased sample?

Accepted Answer

Selecting a sample from property tax records to represent all town residents.

Question 17

Why might a company like NBC hire an independent firm like Nielsen to conduct TV ratings instead of doing it themselves?

Accepted Answer

To avoid bias and provide trustworthy data to advertisers.

Question 18

Which of the following best describes cluster sampling?

Accepted Answer

Dividing the population into groups, randomly selecting some groups, and including all members from those groups in the sample.

Question 19

A study is designed to test the quality of candy bars before shipping. Why is a census not practical in this case?

Accepted Answer

Testing every candy bar would leave none intact to sell.

Question 20

Which of the following is a potential source of bias in medical research publication?

Accepted Answer

Publishing only studies with positive results.

Sampling Methods in Statistics: Concepts, Bias, and Applications

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