Filters
Question type
Study Flashcards

In stratified random sampling, different numbers of cases may be drawn from each stratum.

A) True
B) False

Correct Answer

verifed

verified

In determining the accuracy of sample estimates, the proportion of the population sampled is more important than the absolute size of the sample.

A) True
B) False

Correct Answer

verifed

verified

For a city telephone survey, a sampling frame might consist of the set of all telephone prefixes (first three numbers after the area code) for the city.

A) True
B) False

Correct Answer

verifed

verified

You plan to draw a sample of 1,000 from the population of a large state in order to estimate the average value of individual life insurance coverage. A list of all state residents and their incomes is available from the state revenue department. Which sampling design will minimize sampling error?


A) a simple random sample, using a computer program to generate random numbers
B) a proportionate stratified random sample, using income categories as strata
C) a multistage cluster sample, using counties as clusters
D) a quota sample, with quotas set on the basis of income

E) A) and B)
F) B) and D)

Correct Answer

verifed

verified

The larger the sample, the larger the standard error.

A) True
B) False

Correct Answer

verifed

verified

Probability sampling is always preferable to nonprobability sampling.

A) True
B) False

Correct Answer

verifed

verified

In the National Health and Social Life Survey, "all people aged 18 to 59 with adequate English proficiency living in households located in the 50 states and District of Columbia" describes the


A) target population.
B) sampling frame
C) sample.
D) sampling distribution.

E) All of the above
F) A) and B)

Correct Answer

verifed

verified

Probability sampling enables researchers to calculate the margin of sampling error.

A) True
B) False

Correct Answer

verifed

verified

True

Stratified random sampling is used to __________ ; multistage cluster sampling is used to __________.


A) reduce costs; eliminate the need to list sample elements
B) reduce sampling error; reduce sample size
C) reduce sample size; reduce sampling error
D) reduce sampling error; reduce costs

E) A) and B)
F) A) and C)

Correct Answer

verifed

verified

What defining feature of a simple random sample distinguishes it from other probability sampling designs?


A) It does not require a sampling frame for the selection of cases.
B) Every case is randomly selected.
C) Every case has a known probability of being selected.
D) Every combination of cases has an equal chance of being selected.

E) B) and C)
F) A) and D)

Correct Answer

verifed

verified

Multistage cluster sampling may involve either simple random or stratified random sampling at each stage.

A) True
B) False

Correct Answer

verifed

verified

Probability sampling is to nonprobability sampling as random selection is to nonrandom selection.

A) True
B) False

Correct Answer

verifed

verified

Suppose you use the campus directory to draw a sample of the student population. When you draw your sample you discover that ten students have no telephone number listed; and when you conduct the survey, you discover that five students have an incorrect number listed. These "missing cases" indicate problems with


A) the specification of the target population.
B) the sampling design.
C) the sampling frame.
D) random sampling error.

E) None of the above
F) C) and D)

Correct Answer

verifed

verified

What is the key feature of probability sampling that distinguishes it from nonprobability sampling?


A) selection of very large samples.
B) elimination of sampling error.
C) use of random selection.
D) reduction of bias in the sampling frame.

E) A) and B)
F) A) and C)

Correct Answer

verifed

verified

Which of the following sampling techniques depends for its effectiveness largely on the researcher's knowledge and skill in selecting appropriate cases?


A) convenience sampling
B) simple random sampling
C) purposive sampling
D) multistage cluster sampling

E) None of the above
F) B) and C)

Correct Answer

verifed

verified

Suppose you want to study registered nurses; you are particularly interested in comparing the careers and earning of men and women in this profession. You realize that female nurses outnumber male nurses by a ratio of about 9 to 1. You also discover a national registry of nurses contains a publicly accessible list of all nurses in the U.S. Suppose you have enough funds to draw a sample of 500 for a mail questionnaire survey. a. What would be a good sampling frame for this study? b. Would you choose to use multistage cluster sampling? Briefly explain. c. Why would it be advisable to draw a stratified random sample rather than a simple random sample for your study? d. Suppose you decide to draw a stratified random sample. What information must you have about each respondent in order to draw a stratified random sample? e. Would it be best to use proportionate stratified random sampling or disproportionate stratified random sampling? Briefly explain.

Correct Answer

Answered by ExamLex AI

Answered by ExamLex AI

a. A good sampling frame for this study ...

View Answer

It is best to use probability sampling when


A) trying to understand the context of people's actions.
B) studying a small number of cases.
C) the population is unknown or not readily identifiable.
D) the research objective is to estimate population characteristics.

E) C) and D)
F) A) and B)

Correct Answer

verifed

verified

D

Describe the key differences between probability and nonprobability sampling. What defines a probability sample? For what purposes and under what conditions is it appropriate to use each of these sampling strategies? What kind of inferences are possible with each?

Correct Answer

Answered by ExamLex AI

Answered by ExamLex AI

Probability sampling and nonprobability sampling are two different methods used in research to select a sample from a larger population. The key differences between the two lie in the way the sample is selected and the extent to which the sample represents the population. Probability sampling involves selecting a sample in such a way that every member of the population has a known and non-zero chance of being included in the sample. This method relies on random selection and ensures that the sample is representative of the population. Common types of probability sampling include simple random sampling, stratified sampling, and cluster sampling. On the other hand, nonprobability sampling does not rely on random selection and does not guarantee that every member of the population has an equal chance of being included in the sample. Instead, the sample is selected based on the researcher's judgment or convenience. Common types of nonprobability sampling include convenience sampling, purposive sampling, and quota sampling. A probability sample is defined by its ability to provide unbiased estimates of population parameters, as every member of the population has an equal chance of being included in the sample. This makes probability sampling appropriate for making generalizations about the population and for conducting statistical analyses that require representative samples. Nonprobability sampling, on the other hand, is appropriate when it is not feasible or practical to use probability sampling methods. This may be the case when the population is difficult to access, when time and resources are limited, or when the research question does not require generalizability to the larger population. Nonprobability sampling is often used in exploratory research or when the focus is on understanding specific subgroups within the population. In terms of inferences, probability sampling allows for making statistical inferences about the population, as the sample is representative and unbiased. Nonprobability sampling, on the other hand, limits the ability to make statistical inferences about the population, as the sample may not accurately reflect the population. Instead, nonprobability sampling is more suited for making qualitative or exploratory inferences about the specific sample or subgroup under study. In conclusion, the choice between probability and nonprobability sampling depends on the research question, the characteristics of the population, and the resources available. Probability sampling is ideal for making generalizations about the population and conducting statistical analyses, while nonprobability sampling is more suitable for exploratory research and understanding specific subgroups within the population.

A multistage cluster sample would be most appropriate for an interview study of which of the following populations?


A) all rape victims in your state during the year 2015
B) all students currently enrolled at your college
C) followers of the Grateful Dead rock group
D) all first-year law students in the United States
E) all students at your college who use nonprescription drugs

F) A) and D)
G) A) and C)

Correct Answer

verifed

verified

Increasing sample size from 100 to 500 increases sample precision more than increasing sample size from 1,000 to 5,000.

A) True
B) False

Correct Answer

verifed

verified

Showing 1 - 20 of 89

Related Exams

Exam 1

Introduction

23 Questions

Exam 2

The Nature of Science

73 Questions

Exam 3

Research Ethics

70 Questions

Exam 4

Elements of Research Design

74 Questions

Exam 5

Measurement

82 Questions

Exam 7

Experimentation

75 Questions

Exam 8

Experimental Designs

71 Questions

Exam 9

Survey Research

76 Questions

Exam 10

Survey Instrumentation

67 Questions

Exam 11

Field Research

70 Questions

Exam 12

Research Using Available Data

58 Questions

Exam 13

Multiple Methods

65 Questions

Exam 15

Data Processing and Elementary Data Analysis

72 Questions

Exam 16

Multivariate Analysis

52 Questions

Exam 17

Writing Research Reports

49 Questions

Show Answer