Question 1
1. Disproportionate sampling and weighting are used by the researcher:
a. To ensure a sufficient number of cases in each of the sample subpopulations
b. To give a proportionate representation to each sample element
c. To provide a representative picture of the total population
d. To handle situations involving the errors and approximation that are often inherent in complex, multistage designs
e. To ensure a sufficient number of cases in each of the sample subpopulations; to give a proportionate representation to each sample element; to provide a representative picture of the total population; and to handle situations involving the errors and approximation that are often inherent in complex, multistage designs
Question 2
1. When selecting variables for stratification, it is best to select variables that:
a. Stratify based on gender
b. Stratify based on age
c. Stratify based on the variables you want to represent
d. Stratify in order to achieve equally sized groups
e. Always stratify into at most three groups
Question 3
1. Dr. Smith instructs his graduate students to put together a sample for an upcoming research study of college students. The graduate students are asked to stand outside of the Student Union to solicit participants, finding 50 freshmen, 50 sophomore, 50 juniors, and 50 seniors. What sort of sampling method is being used?
a. Simple random sampling
b. Quota sampling
c. Cluster sampling
d. Stratified sampling
e. Accidental sampling
Question 4
1. The unit about which information is collected and that provides the basis of analysis is called a(n):
a. Universe
b. Sampling unit
c. Statistic
d. Sampling frame
e. Element
Question 5
1. Which of the following is a disadvantage of stratified sampling?
a. It denies you the use of probability theory.
b. It requires you to have some prior knowledge about the elements in the population prior to drawing the sample.
c. It usually increases the standard error.
d. It usually requires samples that are larger in size than those required by simple random sampling.
e. None of these choices.
Question 6
1. Every kth element in a list is chosen for inclusion in the sample in:
a. Simple random sampling
b. Systematic sampling
c. Disproportionate sampling
d. Cluster sampling
e. Stratified sampling
3 points
Question 7
1. Dr. Chang is conducting a research study of undergraduate students at her college. She wants to ensure an equal number of students from each grade level, so she uses the list of all students provided by the registrar’s office. From each list, she randomly selects 50 students from each group. What sampling strategy is Chang using?
a. Simple random sampling
b. Quota sampling
c. Cluster sampling
d. Stratified sampling
e. Accidental sampling
3 points
Question 8
1. You are doing research on hospital personnel—orderlies, technicians, nurses, and doctors. You want to be sure you draw a sample that has cases in each of the personnel categories. You want to use probability sampling. An appropriate strategy would be:
a. Simple random sampling
b. Quota sampling
c. Cluster sampling
d. Stratified sampling
e. Accidental sampling
Question 9
1. Probability samples are advantageous to the researcher because:
a. The method by which they are selected limits conscious and unconscious sampling bias
b. The accuracy or representativeness of the sample can be estimated
c. They are perfectly representative of the population from which they are drawn
d. All of these choices indicate the advantages of probability sampling
e. The method by which they are selected limits conscious and unconscious sampling bias and the accuracy or representativeness of the sample can be estimated
Question 10
1. The chief aim of probability sampling is to be able to select:
a. A sample whose parameters are representative of an unknown population parameter
b. A sample whose statistics will accurately portray an unknown population parameter
c. A sample whose parameters will accurately portray an unknown population statistic
d. A sample whose statistics will accurately portray a known population parameter
e. A sample whose unknown statistics will accurately portray a known parameter