Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students

dc.contributor.authorHamal, Tamanna
dc.contributor.committeeChairMarshall, David
dc.contributor.committeeMemberFalley, Brandi
dc.contributor.committeeMemberEdwards, Don E.
dc.date.accessioned2018-03-19T15:38:54Z
dc.date.available2018-03-19T15:38:54Z
dc.date.issued5/30/2017
dc.description.abstractThe purpose of the study is to compare the Discriminant Analysis and Linear Regression Analysis to predict the correlation between alcohol consumption by high school students and their social attributes and grades. Discriminant Analysis, developed by R. A. Fisher in 1936, is a statistical technique used to determine which variables discriminate between two or more mutually exclusive naturally occurring groups. Linear Regression Analysis is the most widely used statistical technique where straight lines are fitted to patterns of data. In this model, the dependent variable, the variable of interest, is predicted from independent variables using a linear equation. Even though the earliest form of linear regression was the Method of Least Squares, which was published by Legendre in 1805, and by Gauss in 1809, the term regression was pioneered by Sir Francis Galton. Regression analysis is the process of finding out the relationship between one or more dependent variables and the independent variables.en_US
dc.identifier.urihttp://hdl.handle.net/11274/9356
dc.language.isoen_USen_US
dc.subjectPure sciencesen_US
dc.subjectAnalysisen_US
dc.subjectDiscriminanten_US
dc.subjectLinear regressionen_US
dc.subjectSPSSen_US
dc.titleComparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school studentsen_US
dc.typeThesisen_US
thesis.degree.departmentMathematics
thesis.degree.grantorTexas Woman's University
thesis.degree.levelMaster
thesis.degree.nameMaster of Science

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