Final answer:
Standardizing a data set converts raw scores into standardized scores, such as z-scores, which allows for comparison across different tests or variables.
Step-by-step explanation:
Standardizing a data set takes raw scores and turns them into standardized scores. Standardization is a statistical method where scores from different tests or assessments are converted to a common scale.
This allows for comparisons across different tests or variables. Standardizing is often done by calculating the z-score for each data point, which represents how many standard deviations a point is from the mean of the data set.
For instance, if we consider the set of scores 20, 68, 80, and 92, standardization will transform these raw scores into z-scores using the formula: z = (X - μ) / σ, where X is a raw score, μ is the mean of the scores, and σ is the standard deviation. These standardized scores can then be used to compare results across different scales or measurements.