ABCTE Professional Teaching Knowledge Practice Exam

To convert from a raw score to a standard score (also known as a z-score), the mean and standard deviation of the dataset are essential. The standard score indicates how many standard deviations a specific data point (or raw score) is away from the average or mean of the dataset.

To calculate the standard score, you subtract the mean from the raw score and then divide the result by the standard deviation. This transformation allows for a comparison of scores from different datasets or distributions, as it standardizes the scores relative to the mean and variability of the dataset.

The other options, while they contain useful statistical concepts, do not directly relate to the calculation of standard scores. For instance, mode and median focus on measures of central tendency, range and interquartile range pertain to measures of dispersion, and variance and percentile rank serve different statistical purposes but are not used for transforming raw scores into standard scores. Thus, mean and standard deviation are the appropriate calculations needed for this conversion.