What term describes how far an individual score is from the mean?

What term describes how far an individual score is from the mean?

• A. Deviation
• B. Frequency data
• C. Class intervals
• D. Coding

Answer: (A)

The main idea is deviation. A deviation is the difference between a single score and the mean of the dataset, showing how far that score lies from average. If you subtract the mean from the score, you get the deviation; its sign tells you whether the score is above or below the mean, and the magnitude tells you the distance from the mean. In practice, you often look at the absolute value of this difference to describe how far without regard to direction. Related terms like frequency data, class intervals, and coding describe other aspects of data (counts across categories, the ranges used to group data, and converting values into codes), not how far a particular score is from the mean. For a broader sense of typical distance from the mean, standard deviation summarizes the average of these distances (squared and averaged), but the direct distance of an individual score from the mean is a deviation.

The main idea is deviation. A deviation is the difference between a single score and the mean of the dataset, showing how far that score lies from average. If you subtract the mean from the score, you get the deviation; its sign tells you whether the score is above or below the mean, and the magnitude tells you the distance from the mean. In practice, you often look at the absolute value of this difference to describe how far without regard to direction.

Related terms like frequency data, class intervals, and coding describe other aspects of data (counts across categories, the ranges used to group data, and converting values into codes), not how far a particular score is from the mean. For a broader sense of typical distance from the mean, standard deviation summarizes the average of these distances (squared and averaged), but the direct distance of an individual score from the mean is a deviation.