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The SAT is an aptitude test taken by high school juniors and seniors. That is beyond the scope of this tutorial. The calculations to do this make use of canonical correlation, a technique Groups and minimize differences within groups. With multiple discriminant analysis, the goal is to define discriminant functions that maximize differences between The number of group categories minus one - whichever is smaller. The maximum number of discriminant functions will equal the number of predictor variables or Define a second discriminant function to classify non-Democrats as Republicans or Independents.Define one discriminant function to classify voters as Democrats or non-Democrats.Using two-group discriminant analysis, you might: When there are more than two groups, there are also more than two discriminant functions.įor example, suppose you wanted to classify voters into one of three political groups - Democrat, Republican, or Independent. Regression can also be used with more than two classification groups, but the analysis is more complicated. The sample problem at the end of this lesson illustrates each of the above steps Assess the relative importance of predictor variables.Assess the ability of the regression equation to correctly classify observations.Assess the fit of the regression equation to the data.Define regression equation, which is the discriminant function.Other than that, the two-group discriminant analysis is just like standard multiple regression analysis. The biggest difference between discriminant analysis and standard regression analysis is the use of a catergorical variableĪs a dependent variable. The efficacy of the discriminant function is measured by the proportion of correct assignments.The regression equation is called the discriminant function.Observations are assigned to groups, based on whether the predicted score is closer to 0 or to 1.The dependent variable is expressed as a dummy variable (having values of 0 or 1).
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(i.e., a categorical variable that can take on only two values). The dependent variable is a dichotomous, categorical variable.When there are only two classification groups, discriminant analysis is really just multiple regression, with a few tweaks. The approach described in this lesson is based on linear regression.Īdvertisement Two-Group Discriminant AnalysisĪ common research problem involves classifying observations into one of two groups, based on two or more quantitative, predictor variables. Note: There are several different ways to conduct a discriminant analysis. (e.g., minutes of exercise per week, packs of cigarettes per day). (e.g., chololesterol level, body mass) and/or lifestyle behaviors The analysis might classify patients into high- or low-risk groups, based on personal attributes Scores on one or more quantitative predictor variables.įor example, a doctor could perform a discriminant analysis to identify patients at high or low riskįor stroke. Discriminant Analysis Discriminant Analysisĭiscriminant analysis is statistical technique used to classify observations into non-overlapping groups, based on.Linear Regession: Table of Contents Introduction