IBM Data Science Practice Test 2026 – Comprehensive Exam Prep

Question: 1 / 400

What defines an outlier in a dataset?

An observation close to the mean value

An observation that lies an abnormal distance from other values

An outlier in a dataset is defined as an observation that lies an abnormal distance from other values. This means that outliers are significant deviations from the general pattern of the data, which can impact statistical analyses, trends, and interpretations. Outliers can indicate variability in the data, measurement errors, or they might reveal intriguing insights about the studied phenomena. Their identification is crucial, as they can skew results and lead to misleading conclusions if not handled appropriately.

The other options do not align with the definition of an outlier. Observations close to the mean (option A) are well within the data's expected range; frequent observations (option C) indicate commonality rather than deviation; and typical observations (option D) also reflect the normal behavior of the dataset, failing to highlight the extreme deviations characteristic of outliers.

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An observation that is frequently repeated

An observation that is typical of the data range

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