Which type of standard score has a mean of 0 and a standard deviation of 1?

Z-scores are a type of standard score that are specifically designed to indicate how many standard deviations a data point is from the mean of a set of data. By definition, Z-scores have a mean of 0, which signifies that the average score in a normally distributed dataset is centered at this point. Moreover, the standard deviation for Z-scores is set at 1, which allows for a uniform scale when comparing different datasets or distributions.

This standardization process is critical in statistics, as it enables researchers to interpret scores relative to the overall distribution. A Z-score of +1, for example, indicates that the score is one standard deviation above the mean, while a Z-score of -1 indicates that the score is one standard deviation below the mean. This characteristic of Z-scores makes them particularly useful in various statistical analyses, including hypothesis testing and the calculation of probabilities in normal distributions.

On the other hand, raw scores simply represent the original data without any transformation, and T-scores have a mean of 50 and a standard deviation of 10. Percentile ranks show the percentage of scores that fall below a certain value, thus lacking a standardized mean and standard deviation altogether. This lack of standardization makes Z-scores particularly valuable