Descriptive and Inferential Statistics

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Descriptive Statistics is used when describing certain aspects of an immediate group within the population. For example, we may want to describe a math class and compare it to a class of science. Things that we may want to use for comparison would be age, gender, and even math skills. Descriptive statistics would allow us to analyze all those different areas and provide a comparison to view similarities, differences and ratios. Before any study is to be observed certain factors would have to be ascertained such as specific measurements for math skills. Students could possibly complete surveys or be interviewed. Based on the information provided by the students, it would then be possible to describe how certain issues and factors affect students in the class and how variables are related in those classes. However ,the study would be not be generalized to all science and math classes because it would not be a correct depiction of all math and science classes because there are could be a multitude of variables present in different groups of students (California State University, 1998). Inferential statistics are based on a study conducted on a sample of the population that is used to make a general assumption on a wider population. For example, in the United States, a part of the population is sampled at random and that data is used to access the wider population’s voting attitudes. The reason that sampling is done at random in this example, is to prevent any type of bias or prejudice of one American citizen over the other (S.E. Smith, 2010). Descriptive statistics can describe the subset of the population you will study. But to expand your assumptions to a wider population, like all high school classes, all workers, all men, inferential statistics must be used. This means that the sample that is studied has to represent the group you want to generalize to.
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