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Stepwise discriminant analysis is a powerful tool for data preprocessing and analysis, used by researchers and practitioners alike. It is a technique for grouping observations based on their most informative characteristics, using a set of variables that provide the most information. Stepwise discriminant analysis involves a four-step process to select the most informative variables for further analysis: 1. Exploratory Data Analysis: This involves visualizing the dataset to identify patterns and trends. Stepwise selection is based on these visualizations. 2. Initial Cleaning
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Discriminant analysis is a technique used to determine which variables have the most significant relationship to dependent variables. It works by creating a multivariate regression model in which all dependent variables are linked by independent variables, with the most significant relationships at the “right hand side”. Discriminant analysis is a multivariate analysis technique used in a variety of fields including psychology, marketing, and economics. It is used to identify predictors that best describe an independent variable, and which predictors are most important for classifying or grouping respondents or observations into specific
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