Case Study

Based on this scenario, explain how starting with a complete list of all registered voters and ensuring each voter has an equal chance of selection are critical to the concept of simple random sampling. What do these components tell us about the relationship between the sample and the population?

Case context: A pollster is hired to conduct a voting intention survey in a city. The pollster obtains a complete list of all registered voters in the city, which serves as the population. The pollster then uses a computer program to select a sample of 100100 individuals from that list, ensuring that each voter has an equal chance of being chosen.

Question: Based on this scenario, explain how starting with a complete list of all registered voters and ensuring each voter has an equal chance of selection are critical to the concept of simple random sampling. What do these components tell us about the relationship between the sample and the population?

Sample answer: Starting with a complete list of all registered voters ensures that the entire population is represented in the sampling frame, preventing undercoverage. Ensuring that each voter has an equal chance of being chosen is the defining requirement of simple random sampling, which ensures that the sample of 100100 individuals is unbiased and representative of the voter population as a whole.

Key points:

  • A complete list of registered voters represents the entire population.
  • An equal chance of selection is the defining characteristic of simple random sampling.
  • These components prevent selection bias and ensure the sample is representative of the population.

Rubric: Grading criteria: The answer must demonstrate comprehension by explaining that (1) a complete list ensures the entire population is represented, (2) an equal selection probability prevents bias, and (3) these elements combine to ensure the sample is representative of the population.

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Updated 2026-05-27

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Research Methods in Psychology - 4th American Edition @ KPU

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