Explanation

The standard score, which is also called a z-score, is a useful statistic because it gives the statistician a method for calculating the probability of a score occurring within normal distribution (the bell curve). The z-score also allows for comparison of two scores that have different normal distributions.

For example, it would allow a college admission team to compare one student with an SAT test score to another student with an ACT score, even though these are two different knowledge tests. The standard score does this by converting, or standardizing, each of these scores into z-scores. Then the two different scores can be compared.

Step 1

Think of a real-world example. For your post, give a real-life example(s) of data that could be converted to z-scores to give the data meaning.

Offer an example of when you could use a normal curve and compute z-scores in the real world. How would a z-score be useful to compare two different distributions? What would be the advantages? What would be the limitations?