Descriptive vs Inferential Statistics

Welcome, in this post we will explore some of the differences between descriptive and inferential statistics.

Descriptive statistics – can be thought of as stating a fact – it involves organizing, summarizing, and presenting data in a well-laid out and informative way. It uses numbers to describe data.  Examples include bating averages in baseball or height or weight averages in a classroom. There are no extrapolations or assumptions. You’re kind of just dealing with what you already have and know. This includes the past and the present. However it cannot provide information about the future. 

Inferential statistics - takes information about a group (the sample) and applies it to the whole (the population) - allows us to understand or make a prediction about the population through a limited set of data. For example you administer a questionnaire to a group of people and use the results from the sample to make decisions and observations about a population. With inferential statistics you make inferences. This in part is because getting all the data from a population or census may prove impossible, difficult, expensive, time consuming, or destructive. Inferential statistics is fantastic for extrapolating and predicting patterns.