What makes inferential statistics so unique is that if you want to examine one part of a case, you could do so by analyzing the whole issue. For example, you want to know the average performance of all major league baseball teams, but instead of finding it among all of them, choose 15 major league teams that will symbolize a large group of major league baseball teams. Another example according to David D. Barrett, Allen W. Burton and Simon J. Bennett “3,684 pitches thrown by 100 players in 7 collegiate baseball games were examined for location, distance, and active and inactive situations” (Barrett, Burton & Bennett 2002 ). Inferential statistics can be used in many ways, so you could make a decision for your situation and your choice should involve estimating parameters and testing hypotheses. By evaluating parameters and testing hypotheses you will come to conclusions beyond the data you have and making your decision using the data will depend on the type of test you use, for example a t-test or