When we study statistics and applications of statistics, we must include sampling and its effects. It is critical to inference and analytical statistics. As I have stated before, you must have information (data) in order to apply statistics. Suppose we are studying the UMUC student population including thousands of current students as well as past students. We want to produce some interesting information on these students perhaps their success, their income, their opinions, etc. So we start out on the study. Would it be possible to obtain needed information (data) from every student? We will agree the answer is no. Impossible! So what would we usually do in a situation like this? Take a Sample and use that to answer the questions we want to answer. In summary we sample for the following reasons: Necessity -- Sometimes we have no choice. Observing or collecting information from the population is impossible. There are many reasons why this may be the case. Access - We may not have access to the population. All populations are not necessarily "people". We may not know who or what the elements are even though we know generally something about it. Often we do not know the