A data analyst is tasked with evaluating the consistency of two different production lines that manufacture machine screws. The analyst needs to determine which line produces screws with more uniform lengths. To do this, they need to select a statistical measure that quantifies the spread of the data and is expressed in the same unit of measurement (millimeters) as the screw lengths for ease of interpretation. Which of the following measures should the analyst choose?
The correct answer is standard deviation. Standard deviation is a measure of dispersion that quantifies the amount of variation or spread of a set of data values from the mean. A key characteristic and advantage of standard deviation is that it is expressed in the same units as the original data, which makes it easy to interpret. In this scenario, a lower standard deviation in screw lengths for a production line would indicate higher consistency.
Variance is incorrect because, while it also measures data dispersion, its units are the square of the original data's units (e.g., square millimeters). This makes it less intuitive to interpret directly, which contradicts the scenario's requirement for ease of interpretation.
Mean is incorrect as it is a measure of central tendency, not dispersion. It calculates the average value but provides no information about the consistency or spread of the data.
Range is incorrect because, while it is a simple measure of spread and is in the same units, it only considers the minimum and maximum values. It is sensitive to outliers and does not provide as comprehensive a measure of overall consistency as standard deviation.
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CompTIA Data+ DA0-002 (V2)
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