A researcher uses a computer to obtain a sample of city residents so each resident has an equal chance of being selected. Which sampling method is being used?
Simple random sampling is being used.
This method ensures that every resident in the city has an equal chance of being selected, thereby eliminating biases and enhancing the representativeness of the sample.
Judgment sampling involves selecting individuals based on the researcher’s subjective judgment rather than a random process. This method does not guarantee that each resident has an equal chance of being selected, potentially leading to biased results that do not accurately represent the population.
Convenience sampling refers to selecting individuals who are easiest to reach, such as those readily available or nearby. This method fails to provide equal chances for all residents to be selected and can result in a non-representative sample that overlooks diverse perspectives within the population.
Stratified sampling is a method where the population is divided into distinct subgroups (or strata) and random samples are taken from each stratum. While this technique aims to ensure representation of various segments of the population, it does not involve giving each individual an equal chance of selection across the entire population as simple random sampling does.
In simple random sampling, each individual in the population has an equal chance of being chosen, which is precisely what the researcher is doing by using a computer to obtain a sample of city residents. This method is recognized for its ability to minimize selection bias and ensure a representative sample.
Simple random sampling is characterized by the equal likelihood of selection for each individual in the population, making it an effective method for obtaining unbiased samples. In this scenario, the researcher’s use of a computer to randomly select city residents exemplifies this technique, distinguishing it from other sampling methods that do not provide equal selection opportunities.
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