Overall, statistics can be divided into two main categories. They are descriptive and inferential. They are different, but both are important in the field of social science. Both descriptive and inferential statistics can help social scientists obtain a snapshot of a given population or sample of a population. The crux of the differences between descriptive and inferential statistics is how they are defined, how they are applied by social scientists, and the amount of care a social scientist must take in using them. Descriptive statistics were defined by C. Urdan (2010) as “statistics used to describe the characteristics of a distribution of scores” (p. 10). An addition to this definition is the fact that descriptive statistics “summarize data with the purpose of describing what happened in the sample” (Allua & Thompson, 2009). Descriptive statistics are literally just the numbers for that population or sample. An example of this is saying that “suicide is a major factor [in premature deaths of people with mental illnesses], accounting for 30 to 40% of premature deaths. 60% die from preventable or treatable conditions” (Garey, 2013) , descriptive statistics do not draw conclusions about the data collected, it is just about what is collected. Inferential statistics are “statistics, derived from sample data, that”. they are used to make inferences about the population from which the sample was drawn” (Urdan, 2010, p. 11). Inferential statistics “refers to the use of sample data to reach some conclusions (i.e., make some inferences) about the characteristics of the larger population that the sample is supposed to represent” (Urdan, 2010, p. 2). An example of inferential statistics statistics would say "9... half of the paper... Scientists and the amount of care a social scientist must take to use them correctly. It is important to know the distinctions between descriptive and inferential statistics because without knowing the differences, a social scientist may run the risk of misusing the data collected. Proper use of data is critical to being a good social scientist and helps advance the field of social science. Works CitedAllua, S., & Thompson , C.B. (2009). Air Medical Journal, 28(4), 168-171. New York, NY. Taylor & Francis Group. Garey, J. (2013, August 10). When Doctors Discriminate. May, C., & Post, J. (2013). Psychiatric News. doi: 10.1176/appi.pn.2013.3b27