Z-scores explained with a sweet example: using candy to understand standard scores 🍬
A z-score, also known as a standard score, is a measure of how many standard deviations an element is from the mean. In other words, it tells you how far a value is from the average value in a dataset.
Here’s an example using candy:
let’s say you have a bag of candy that contains 10 pieces of candy, and the average weight of a piece of candy is 10 grams. If one of the pieces of candy in your bag weighs 15 grams, its z-score would be (15–10)/10 = 0.5. This means that the candy is 0.5 standard deviations above the average weight.
One reason why you might want to use a z-score in this situation is to determine whether the piece of candy is unusually heavy compared to the other pieces in the bag. For example, if you know that the standard deviation of candy weights is relatively small, a z-score of 0.5 might indicate that the 15-gram candy is significantly heavier than the other pieces.
In general, z-scores are useful for comparing the relative size of an element in a dataset to the other elements in the dataset. They can be used in a variety of applications, such as education, finance, healthcare, sports, and psychology, to compare an individual value to the average values in a population.
