A data analyst studies a random sample of 200 retail transactions to estimate the average purchase amount across many locations. The analyst wants a range that reflects how the calculated average would vary if different samples were taken, at a specific level of certainty. Which method is the most appropriate to achieve the analyst's objective?
Perform a correlation test on purchase quantities and store IDs
Obtain a probability (p-value) for the observed sample mean
Use a confidence interval that includes the sample mean and accounts for sampling variability
Identify the highest and lowest purchase amounts in the sample
Constructing a confidence interval (CI) produces a range around the sample mean that accounts for variability, offering a measure of how well the sample statistic might represent the actual population mean. Using maximum and minimum values does not capture sampling error. A p-value focuses on hypothesis testing rather than interval estimates. Measuring correlation is suited for assessing relationships between variables, not interval estimation of a single average.
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