Chat with AIExam 6: Sampling
It is best to use probability sampling when
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Probability sampling enables researchers to calculate the margin of sampling error.
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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?
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Answered by Examlex AI CopilotProbability 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.
Probability sampling is to nonprobability sampling as random selection is to nonrandom selection.
(29) Multistage cluster sampling may involve either simple random or stratified random sampling at each stage.
(40) 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.
(41) What is the key feature of probability sampling that distinguishes it from nonprobability sampling?
(27) What defining feature of a simple random sample distinguishes it from other probability sampling designs?
(41) Probability sampling is always preferable to nonprobability sampling.
(37) A multistage cluster sample would be most appropriate for an interview study of which of the following populations?
(34) Stratified random sampling is used to __________ ; multistage cluster sampling is used to __________.
(36) 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?
(30) 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
(35) Increasing sample size from 100 to 500 increases sample precision more than increasing sample size from 1,000 to 5,000.
(29) In stratified random sampling, different numbers of cases may be drawn from each stratum.
(37) 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.
(32) 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
(29) In determining the accuracy of sample estimates, the proportion of the population sampled is more important than the absolute size of the sample.
(39) Which of the following sampling techniques depends for its effectiveness largely on the researcher's knowledge and skill in selecting appropriate cases?
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