statistics

Measures of variability are essential to inferential statistics because they provide a measure of how much scatter or spread there is in the data. Since inferential statistics use sample data to make inferences about the underlying population, it is important to understand how much variability exists in the data and how confident we are in our predictive conclusions. Measures of variability help us understand the amount of uncertainty associated with our predictions. For example, if a study is looking at the amount of time people spend on their phone each day, the sample's mean and standard deviation can be used to get a sense of how much time the population as a whole spends on their phone each day, and how reliable the predictions are.