Truncation (statistics)

Truncation in statistics means that we only look at the data that falls below or above a certain value. Imagine you have a big bag of candy and you only want to look at the candy that is red. You would put a filter on the bag and only keep the candy that is red, throwing away all the other colors. It's like putting blinders on a horse so they can only see what is right in front of them.

For example, if we want to study the height of people in a certain age group, we might decide to only look at those who are shorter than 6 feet. This means we are truncating the data by cutting off those who are taller than 6 feet.

Truncation can be used to create a more focused or specific data set, but it's important to be careful when doing this because it can also lead to bias in the results. It's like looking at a tiny piece of a puzzle and trying to figure out what the whole picture looks like. You might miss important details because you're not looking at the full picture.