To identify which situation describes a dataset that contains an outlier, we should look for scenarios where there could be extreme values that deviate significantly from the rest of the data.
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The salaries at a Fortune 500 company - This dataset might contain outliers, as executives may earn much higher salaries than typical employees.
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The caloric intake of an individual who follows a meal plan - This is less likely to have outliers, as meal plans are usually designed to be within a certain range of caloric intake.
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A teacher’s daily step count - This could potentially include outliers, particularly if the teacher has a day with extremely low or high activity compared to their usual count.
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The number of cars parked at a parking garage on weekdays - This should generally follow a normal range, although special events could potentially cause outliers on particular days.
Given these considerations, the salaries at a Fortune 500 company is most likely to contain outliers due to large income variances among employees.