Observations from a dataset show one elevated region, with the majority of values extending evenly on both sides. Which method best captures what is typical and how far values extend?
Rely on the midrange and a partial segment of the dataset’s values to represent the core behavior.
Compute the arithmetic average plus a measure of distance from that average to portray the center and spread.
Use the middle value along with the difference between the smallest and largest points to gauge overall variability.
Gather frequencies of each value, then rely on the most frequent count to indicate the primary measurement.
When data extend evenly from a central region, the arithmetic average (mean) and the typical distance from that average (standard deviation (SD)) effectively describe both the center of the distribution and its spread. Measuring frequencies or using the median and an overall range can mask important details. Pairing the midrange with a partial range measure can overlook how values cluster around the central region. The mean and SD together highlight both the central location and how values diverge from it.
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What are the limitations of using median and range for data description?