Term Paper: Chi-Square Analysis: The History, Development, and Applicability of a Common Statistical Tool

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Chi Square

An Overview of Chi-Square Analysis: The History, Development, and Applicability of a Common Statistical Tool

There are many different types of information available in the world, and each type can be utilized in very different and highly specific ways depending on both the form of the information and the needs of those utilizing it. These types of information are, in some perspectives, classified into two broader types of information: quantitative and qualitative. Quantitative information is information the can essentially be boiled down to numeric form, and can arise out of either counting or measurement, leading to discrete or continuous data points that can be further analyzed and manipulated to result in deeper understandings of quantifiable phenomena and events. Qualitative data, on the other hand, cannot be reduced to numbers and must be analyzed through other means. Statistics has developed as a field of mathematics that enables researchers to analyze both quantitative and qualitative information in a way that allows for their comparison and analysis in many different ways.

The Chi-Square analysis is one statistical tool that has been developed as a way of analyzing and manipulating qualitative data. Specifically, the Chi Square method was developed in order to compare categorical data in order to determine what type of relationship existed between different qualitative variables (HWS 2010). A drug trial, for instance, might want to compare the number of people receiving a drug to the rates at which their symptoms improved when compared to another group not taking the drug -- the Chi Square analysis test would be a necessary tool in determining the drug's true efficacy.

There are actually several different types of Chi Square analysis that can be utilized, depending on the needs and scope of the research, but the most common of these is the Pearson's Chi-Square test. Karl Pearson was a scientist, philosopher, and mathematician of some renown both during and after his day, and his development of a specific method for analyzing the goodness of fit of a sample distribution and for testing the independence of certain variables/phenomenon (as in the drug trial example given above) is only one of his contributions to the worlds of science and data analysis (Plackett 1983). In 1900, he began working with the Chair of Zoology at the University College of London who supplied a great deal of data to Pearson at a time when his decade of work in correlation (methods of determining the degree to which separate observations occurred together or specifically in the other's absence, suggesting some relationship) and regression analyses (determining the relationship(s) between two or more independent variables on an independent variable) were culminating into the method… [END OF PREVIEW]

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Chi-Square Analysis: The History, Development, and Applicability of a Common Statistical Tool.  (2010, February 27).  Retrieved September 20, 2019, from https://www.essaytown.com/subjects/paper/chi-square-analysis-history-development/7837

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"Chi-Square Analysis: The History, Development, and Applicability of a Common Statistical Tool."  27 February 2010.  Web.  20 September 2019. <https://www.essaytown.com/subjects/paper/chi-square-analysis-history-development/7837>.

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"Chi-Square Analysis: The History, Development, and Applicability of a Common Statistical Tool."  Essaytown.com.  February 27, 2010.  Accessed September 20, 2019.
https://www.essaytown.com/subjects/paper/chi-square-analysis-history-development/7837.