Test Bank

Chapter 5: Sampling

Multiple Choice

1. The set of individuals or other entities to which we want to be able to generalize our findings is the ______.

a. sample

b. subset

c. population

d. sampling frame

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Knowledge

Answer Location: Sample Planning

Difficulty Level: Easy

2. A subset of the larger set of individuals or other entities in which we are interested is the ______.

a. component

b. population

c. elementary unit

d. sample

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Knowledge

Answer Location: Sample Planning

Difficulty Level: Easy

3. Dr. Jones is researching perception of student safety at East High School. She will obtain the sample directly from the entire population of students at the school based on a list obtained from the registrar’s office. This list, from which the elements of the population are selected, is termed the ______.

a. elementary unit

b. sampling frame

c. sample subset

d. enumeration unit

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Knowledge

Answer Location: Define Sample Components and the Population

Difficulty Level: Easy

4. Sampling is unnecessary if ______.

a. all the units in the population are identical

b. most of the units in the population are identical

c. social scientists are able to skirt the problem of generalizability

d. the research population is very diverse

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Assess Population Diversity

Difficulty Level: Easy

5. ______ generalizability refers to the ability to generalize from a sample of a larger population to that population itself.

a. Cross-population

b. Sample

c. Internal

d. External

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Evaluate Generalizability

Difficulty Level: Comprehension

6. In some circumstances, researchers can bypass the issue of generalizability by conducting a(n) ______.

a. interview of key members of the population

b. survey

c. telephone survey

d. census

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Comprehension

Answer Location: Consider a Census

Difficulty Level: Medium

7. Sampling methods that let us know in advance how likely it is that an element of a population will be selected for the sample are ______ sampling methods.

a. nonprobability

b. probability

c. systematic bias

d. stratified

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Sampling Methods

Difficulty Level: Medium

8. A major hazard in survey research may occur because individuals who ______.

a. respond too quickly to surveys are likely not to complete the survey

b. are selected randomly from a population are likely not to be generalizable to the population from which they are drawn

c. are chosen from a complete sampling frame and may therefore not complete the survey

d. do not respond to a survey are likely to differ systematically from those who take the time to participate

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Sampling Methods

Difficulty Level: Medium

9. Sampling error can generally be defined as the ______.

a. difference between the characteristics of a sample and the characteristics of the population from which it was selected

b. similarities between a population and a sample

c. set of elements larger than or different from the population that was sampled

d. difference between the elements of a sample and the elements of a related population

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

10. The target population consists of a set of elements ______.

a. smaller than or different from the population that was sampled, to which the researcher would like to generalize any study findings

b. larger than or different from the population that was sampled, to which the researcher would like to generalize any study findings

c. smaller than or the same size as the population from which it was sampled, that is representative of the population

d. larger than or the same size as the population from which it was sampled, that is not representative of the population

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

11. Sampling methods in which the probability of selection of population elements is unknown are known as ______ sampling methods.

a. representative

b. probability

c. nonprobability

d. unrepresentative

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Sampling Methods

Difficulty Level: Easy

12. In the National Intimate Partner and Sexual Violence Survey (NISVS), adult U.S. residents were selected through a ______ sampling method.

a. random digited dialing

b. stratified random

c. proportionate random

d. random digit dialing

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Simple Random Sampling

Difficulty Level: Medium

13. A situation where the sequence of elements varies in some regular, periodic pattern is known as ______.

a. stratification

b. periodicity

c. replacement sampling

d. cluster sampling

Learning Objective: 5.4: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Systematic Random Sampling

Difficulty Level: Medium

14. In disproportionate stratified sampling, the proportion of each stratum is ______ what is in the population.

a. slightly varied from

b. intentionally varied from

c. proportionally stratified from

d. selected in exact proportion to

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Application

Answer Location: Stratified Random Sampling

Difficulty Level: Hard

15. Cluster sampling can be useful when ______.

a. a sampling frame is not available

b. the population is spread across a narrow geographic area

c. sampling procedures are not complex

d. elements within the population do not have a known probability

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Multistage Cluster Sampling

Difficulty Level: Medium

16. Nonprobability sampling methods are often used ______.

a. when a small sample allows a more intensive portrait activities and actors in a population

b. if there is a clear chance of elements being chosen

c. when we can generalize findings to a larger population

d. if there is a large population that covers a huge territory

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Nonprobability Sampling Methods

Difficulty Level: Medium

17. In ______ sampling, elements are selected because they are easy to find.

a. simple random

b. availability

c. cluster

d. snowball

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Availability Sampling

Difficulty Level: Easy

18. ______ sampling is intended to overcome the likelihood that the sample will just consist of who or what is available.

a. Simple random

b. Stratified random

c. Quota

d. Accidental

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Quota Sampling

Difficulty Level: Medium

19. ______ sampling may involve studying an entire population or some subset of a population.

a. Purposive

b. Accidental

c. Quota

d. Simple random

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Comprehension

Answer Location: Purposive or Judgment Sampling

Difficulty Level: Medium

20. In their classic book Crimes of the Middle Class, Weisburd, Wheeler, Waring, and Bode (1991) examined a sample of white-collar criminal offenders convicted in seven federal judicial districts, using ______ sampling.

a. simple random

b. stratified random

c. quota

d. purposive

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Purposive or Judgment Sampling

Difficulty Level: Hard

21. In criminological research, the units under study are known as the units of ______.

a. analytics

b. isolationism

c. analysis

d. randomness

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Application

Answer Location: Units of Analysis and Errors in Causal Reasoning

Difficulty Level: Medium

22. In their classic study of neighborhoods and crime, Sampson, Raudenbush, and Earls (1997) surveyed individuals and then averaged those responses to create a construct at the neighborhood level called “collective efficacy.” The units of analysis they used was at the ______ level.

a. individual

b. group

c. neighborhood

d. nation

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Application

Answer Location: Units of Analysis and Errors in Causal Reasoning

Difficulty Level: Medium

23. A researcher who draws conclusions about individual-level processes from group-level data is constructing a(n) ______ fallacy.

a. individual level

b. ecological

c. reductionist

d. analytical

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Analysis

Answer Location: The Ecological Fallacy and Reductionism

Difficulty Level: Hard

24. When data about individuals are used to make inferences about group-level processes, this problem creates a(n) ______ fallacy.

a. individual level

b. ecological

c. reductionist

d. analytical

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Comprehension

Answer Location: The Ecological Fallacy and Reductionism

Difficulty Level: Medium

25. Observations based on faulty perceptions of empirical reality are also known as ______ observations.

a. unbelievable

b. elemental

c. enumeration

d. inaccurate

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Sample Planning

Difficulty Level: Easy

26. The ability to generalize from findings about one group, population, or setting to other groups, populations, or settings is known as ______.

a. crossed sample generalizability

b. sample validation

c. cross-population generalizability

d. resource generalizability

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Comprehension

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

27. A sample that looks similar to the population from which it was selected in all respects that are potentially relevant to the study is known as a(n) ______ sample.

a. representative

b. irrepressible

c. reformed

d. unknowable

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Comprehension

Answer Location: Assess Population Diversity

Difficulty Level: Medium

28. Sample generalizability depends on sample quality, which is determined by the ______.

a. similarities of the characteristics of a sample and the population from which it came

b. size of the sampling error

c. consistency of sampling error

d. set of elements to which the sample is to be generalized

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Comprehension

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

29. A major hazard in survey research is ______ because those who do not respond to a survey are likely to differ systematically from those who do.

a. random

b. nonresponse

c. quantity

d. generalizability

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Consider a Census

Difficulty Level: Medium

30. Sampling methods that do not reveal the likelihood of selection in advance are likely to ______.

a. be probability sampling methods

b. have serious methodological issues

c. have a natural tendency to confuse the concept of probability

d. be nonprobability sampling methods

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Sampling Methods

Difficulty Level: Easy

31. Simple random sampling requires a procedure that generates numbers or identifies cases ______.

a. through differentiation of value based on strata

b. strictly on the basis of chance

c. by using disproportionate stratified sampling

d. strictly on the basis of periodicity

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Knowledge

Answer Location: Simple Random Sampling

Difficulty Level: Easy

32. Stratified random sampling differentiates all elements in the population on the basis of their value on some relevant characteristic, and then they are ______.

a. sorted into positive and negative forms of the element

b. disproportionately sampled within each stratum

c. sampled randomly from within these strata

d. put into a random digit dialing program to properly sample them

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Application

Answer Location: Stratified Random Sampling

Difficulty Level: Medium

33. The U. S. Justice Department’s National Crime Victimization Survey is an excellent example of a(n) ______ sample.

a. nonprobability

b. cluster

c. simple random

d. stratified

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Multistage Cluster Sampling

Difficulty Level: Medium

34. Unlike probability samples, when collecting a sample using nonprobability sampling techniques, elements within the population ______.

a. are certain to be a sample which actually represents the population

b. uses information known about the total population prior to sampling to make the sampling process more efficient

c. do not have a known probability of being selected into the sample

d. requires a procedure that generates numbers or identifies cases strictly on the basis of chance

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Nonprobability Sampling Methods

Difficulty Level: Medium

35. ______ sampling is useful for hard-to-reach populations for which there is no sampling frame, but in which the members are somewhat interconnection (at least some members of the population know each other such as drug dealers, sex workers, and so on).

a. simple random

b. stratified random

c. purposive

d. snowball

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Snowball Sampling

Difficulty Level: Medium

True/False

1. Probability sampling methods depend on nonrandom selection procedures.

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Sampling Methods

Difficulty Level: Easy

2. In a census, of all the elements of a population, the probability that any particular element will be selected is 1.0.

Learning Objective: 3.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Sampling Methods

Difficulty Level: Medium

3. Units selected at each stage of a multistage sample design are known as sampling units.

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Sample Planning

Difficulty Level: Easy

4. Cross-population generalizability refers to the ability to generalize from a sample (subset) of a larger population to that population itself.

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Evaluate Generalizability

Difficulty Level: Easy

5. Probability sampling methods are those in which the probability of selection is known and not zero.

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Probability Sampling Methods

Difficulty Level: Easy

6. When selecting or evaluating a sample, the researcher must understand exactly what population they represent.

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Comprehension

Answer Location: Define Sample Components and the Population

Difficulty Level: Medium

7. In simple random sampling, every sample element is selected only on the basis of chance through a random process.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Knowledge

Answer Location: Probability Sampling Methods

Difficulty Level: Easy

8. Including cell phone numbers in a phone survey can introduce bias.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Simple Random Sampling

Difficulty Level: Medium

9. Systematic random sampling is a convenient method for drawing a random sample when the population elements are not arranged sequentially.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Application

Answer Location: Systematic Random Sampling

Difficulty Level: Medium

10. To avoid sampling bias, we could create a list of convicted felons sorted by offense type, age, or some other characteristic of the population.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Systematic Random Sampling

Difficulty Level: Medium

11. Simple random sampling uses information known about the total population prior to sampling to make the sampling process more efficient.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Stratified Random Sampling

Difficulty Level: Medium

12. Because each stratum is represented exactly in proportion to its size in the population from which the sample is drawn, by using proportionate stratified sampling you would eliminate any possibility of error in distribution of a variable.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Stratified Random Sampling

Difficulty Level: Medium

13. Multistage cluster sampling requires less prior information than stratified sampling.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Application

Answer Location: Multistage Cluster Sampling

Difficulty Level: Medium

14. Drawing a cluster sample is a one-stage procedure.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Knowledge

Answer Location: Multistage Cluster Sampling

Difficulty Level: Easy

15. A cluster is a naturally occurring, mixed aggregate of elements of the population.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Knowledge

Answer Location: Multistage Cluster Sampling

Difficulty Level: Easy

16. When collecting a sample using nonprobability sampling techniques, elements within the population have a known probability of being selected into the sample.

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Knowledge

Answer Location: Nonprobability Sampling Methods

Difficulty Level: Easy

17. Availability samples are generalizable to a larger population.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Knowledge

Answer Location: Availability Sampling

Difficulty Level: Easy

18. Dr. Poldark is using availability sampling when she has her students complete a short questionnaire at the end of class.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Comprehension

Answer Location: Availability Sampling

Difficulty Level: Medium

19. Quota sampling is intended to overcome availability sampling’s biggest downfall.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Comprehension

Answer Location: Quota Sampling

Difficulty Level: Hard

20. Quota sampling is another name for judgment sampling.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Knowledge

Answer Location: Purposive or Judgment Sampling

Difficulty Level: Easy

21. St. Jean (2007) used purposive sampling for recruiting offenders in a Chicago neighborhood for research about the logic offenders used for setting up street drug dealing and staging robberies.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Snowball Sampling

Difficulty Level: Medium

22. The more homogeneous the population, the more confidence we can have in the representativeness of a sample of any particular size.

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Probability Sampling Methods

Difficulty Level: Medium

23. A researcher who draws conclusions about group-level processes from individual-level data is constructing an ecological fallacy.

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Application

Answer Location: The Ecological Fallacy and Reductionism

Difficulty Level: Medium

24. When data about individuals are used to make inferences about group-level processes, a problem occurs, known as the reductionist fallacy.

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Application

Answer Location: The Ecological Fallacy and Reductionism

Difficulty Level: Medium

25. Purposive sampling is a method of sampling in which sample elements are selected as they are identified by successive informants or interviewees.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Comprehension

Answer Location: Snowball Sampling

Difficulty Level: Medium

Short Answer

1. Dr. Smithson is interested in whether students at East High School in Columbus, Ohio, feel safe while they are on their way to and from school, and while at school. He contacts the school, and arranges to go to several classrooms to distribute a survey regarding perception of safety. Why would it not be appropriate to generalize findings to all high schools in Columbus?

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Comprehension

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

2. What two ways does Schofield (2002) suggest for increasing the generalizability of samples in nonprobability sampling methods in qualitative research?

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Generalizability in Qualitative Research

Difficulty Level: Medium

3. Generalizability has two aspects. What are they? As part of your answer, name, describe, and provide an example for each.

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

4. When is sampling unnecessary? What assumptions must be made? What are the potential problems with these assumptions?

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Application

Answer Location: Assess Population Diversity

Difficulty Level: Medium

5. What is a Census? Provide an example of a census. How does it affect the issue of generalizability? Why is it that social scientists don’t use them more often?

Learning Objective: 5.1: Identify the circumstances that make sampling unnecessary and the reason they are rare.

Cognitive Domain: Comprehension

Answer Location: Consider a Census

Difficulty Level: Medium

6. What is the purpose of sampling? As part of your answer, define sample, population, sampling frame, and sample elements.

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Define Sample Components and the Population

Difficulty Level: Easy

7. What is the difference between probability and nonprobability sampling? How does each relate to sample generalizability?

Learning Objective: 5.3: Define and distinguish probability and nonprobability sampling and both techniques’ relationship to sample generalizability.

Cognitive Domain: Comprehension

Answer Location: Sampling Methods

Difficulty Level: Medium

8. How does sampling error relate to sample generalizability?

Learning Objective: 5.2: Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality.

Cognitive Domain: Knowledge

Answer Location: Evaluate Generalizability

Difficulty Level: Medium

9. Describe simple random sampling.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Simple Random Sampling

Difficulty Level: Medium

10. What is systematic random sampling? What are the required steps?

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Systematic Random Sampling

Difficulty Level: Medium

11. Describe stratified random sampling. Why is it more efficient than simple random sampling?

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Comprehension

Answer Location: Stratified Random Sampling

Difficulty Level: Medium

12. Why would the use of stratified random sampling be more efficient than simple random sampling? Why might it be more representative of smaller groups within a population? As part of your answer, discuss the use of proportionate and disproportionate stratified sampling.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Application

Answer Location: Stratified Random Sampling

Difficulty Level: Medium

13. When is cluster sampling useful? As part of your answer, describe multistage cluster sampling.

Learning Objective: 5.4: Define the major types of probability sampling, and indicate when each is preferred.

Cognitive Domain: Application

Answer Location: Multistage Cluster Sampling

Difficulty Level: Hard

14. Name and describe four types of nonprobability sampling methods.

Learning Objective: 5.5: Explain when nonprobability sampling methods may be preferred.

Cognitive Domain: Application

Answer Location: Nonprobability Sampling Methods

Difficulty Level: Medium

15. What are Units of Analysis? Why are they important? How can errors be made when generalizing from one unit of analysis to another?

Learning Objective: 5.6: Understand what units of analysis are and how errors can be made when generalizing from one unit of analysis to another.

Cognitive Domain: Application

Answer Location: Units of Analysis and Errors in Causal Reasoning

Difficulty Level: Hard