What are scores expressed along a scale where the mean and standard deviation have been set at certain values called?

Scores that are expressed along a scale with predetermined mean and standard deviation are commonly known as standard scores. Standard scores allow for the comparison of individual scores to a normative distribution. They are calculated by transforming raw scores into a format that reflects how far each score is from the mean, standardized by the standard deviation of the distribution.

Standard scores have the advantage of making it easier to interpret an individual’s performance relative to others, as they are measured in a consistent manner. In many cases, standard scores are set so that the mean is 0 and the standard deviation is 1, allowing for clearer insights into the position of an individual score within a distribution.

On the other hand, raw scores represent the original, unmodified data and lack contextual information. Z-scores, specifically, are a type of standard score that measure how many standard deviations a data point is from the mean but do not encompass all standard score systems. T-scores are another form of standard scores that have a mean of 50 and a standard deviation of 10, thus falling under the umbrella of standard scores but being more specific. Therefore, standard scores represent the broader category that includes both z-scores and t-scores, making it the most encompassing term in this context.