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    Question

    Which of the following is the most important reason for

    calculating the sample size correctly in data analysis?
    A To ensure the sample includes every possible outcome from the population. Correct Answer Incorrect Answer
    B To minimize the risk of underrepresentation and improve statistical power. Correct Answer Incorrect Answer
    C To simplify the data collection process by reducing the number of respondents. Correct Answer Incorrect Answer
    D To ensure the analysis is biased toward a particular segment of the population. Correct Answer Incorrect Answer
    E To make data cleaning more efficient and effective. Correct Answer Incorrect Answer

    Solution

    Calculating the correct sample size is crucial because it directly impacts the reliability and validity of the analysis. A sample that is too small may not accurately represent the population, leading to underrepresentation of key subgroups and insufficient statistical power to detect significant differences or trends. A properly sized sample ensures that the results are reliable and that the findings can be generalized to the population. Statistical power is essential to determine the likelihood that a true effect will be observed, reducing the risk of Type II errors (failing to detect a true effect when one exists). The other options are incorrect because: • Option 1 (Including every possible outcome) is unrealistic and unnecessary in sampling, as sampling involves working with a subset, not the whole population. • Option 3 (Simplification) overlooks the importance of ensuring that the sample is large enough to draw valid conclusions. • Option 4 (Bias toward a segment) is undesirable, as sample size calculation aims to avoid bias and ensure representativeness. • Option 5 (Data cleaning) relates to dataset preparation but is not directly influenced by the sample size calculation itself.

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