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Sample size determination relies heavily on the desired confidence level (e.g., 95%) and acceptable margin of error (e.g., ±5%). These factors ensure the sample provides reliable and precise estimates about the population. A smaller margin of error requires a larger sample size. Tools like power analysis or sample size calculators often use these parameters to calculate the minimum sample size needed for statistical validity. Why Other Options Are Wrong : A) While resources influence feasibility, they shouldn’t dictate sample size at the cost of accuracy. C) Total population size impacts sample size minimally beyond a certain threshold. D) Sampling technique affects how a sample is drawn, not its size. E) The number of variables might influence data collection but isn’t the primary determinant of sample size.
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