Question
Match the name of the sampling method descriptions given.
Situations
a. Simple Random
b. Convenience
c. Stratified
d. Systematic
e. Cluster
Situations
a. Simple Random
b. Convenience
c. Stratified
d. Systematic
e. Cluster
Ask by Mann Floyd. in the United States
Mar 21,2025
Upstudy AI Solution
Tutor-Verified Answer
Answer
- Pulling 50 names from a hat: Simple Random
- Separating students by grade and selecting 10 from each: Stratified
- Asking all students in your math class: Convenience
- Choosing every 5th person on a list: Systematic
- Dividing population by voting precincts and sampling everyone in selected precincts: Cluster
Solution
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For “pulling 50 names from a hat”:
- Every individual has an equal chance of being selected, which is characteristic of a simple random sample.
- Answer:
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For “separating all students by grade level, and selecting 10 students from each grade”:
- The population is divided into mutually exclusive subgroups (strata) and a sample is taken from each, which defines stratified sampling.
- Answer:
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For “ask all the students in your math class”:
- Choosing a sample based on ease of access (the students you already have in your math class) is typical of convenience sampling.
- Answer:
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For “choosing every 5th person on a list”:
- The method of selecting every
th individual from a list is an example of systematic sampling. - Answer:
- The method of selecting every
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For “dividing by population by voting precinct, and sampling everyone in the precincts selected”:
- Dividing the population into natural clusters (voting precincts) and then sampling all individuals within selected clusters is known as cluster sampling.
- Answer:
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Simplify this solution Beyond the Answer
Pulling 50 names from a hat would be classified as a Simple Random sampling method. This example perfectly illustrates the essence of randomness since every student has an equal chance of being selected, making it a classic method for unbiased sampling.
Separating all students by grade level and selecting 10 students from each grade exemplifies Stratified sampling. This approach ensures representation across different groups, allowing researchers to capture a more comprehensive view of the population’s dynamics, such as how different grades may influence certain behaviors or attitudes.
