Strategy for Complete Discriminant AnalysisAssumptions of normality, linearity, and homogeneity of varianceAssumption of linearity in discriminant analysisAssumption of homogeneity of variance - 1Assumption of homogeneity of variance - 2Detecting outliers in discriminant analysis - 1Detecting outliers in discriminant analysis - 2Detecting outliers in discriminant analysis - 3Detecting outliers in discriminant analysis - 4Detecting outliers in discriminant analysis - 5MulticollinearityValidationOverall strategy for solving problemsDiscriminant analysis – stepwise variable entryLevel of measurement - answerSample size requirementsThe stepwise discriminant analysis – baseline modelSelecting the dependent variableDefining the group valuesCompleting the range of group valuesSpecifying the method for including variablesRequesting statistics for the outputSpecifying statistical outputSpecifying details for the stepwise methodDetails for the stepwise methodSpecifying details for classificationDetails for classification - 1Details for classification - 2Details for classification - 3Completing the discriminant analysis requestSample size – ratio of cases to variables evidence and answerSample size – minimum group size evidence and answerClassification accuracy before transformations or removing outliersAssumption of normality of independent variable - questionTest Assumption of Normality with ScriptAssumption of normality of independent variable – evidence and answerSlide 37Slide 38Slide 39Slide 40Slide 41Detection of outliers - questionDetecting outliersUsing SPSS to calculate the critical value for Mahalanobis D²The number of variables used to compute Mahalanobis D²Computing the critical value for Mahalanobis D²Selecting the SPSS functionCompleting the function argumentsThe critical value for Mahalanobis D²Skipping ungrouped casesIdentifying outliersSelecting the model to interpretThe caseid of the outlierOmitting the outliersSpecifying the condition to omit outliersThe formula for omitting outliersCompleting the request for the selectionThe omitted outlierSelecting the model to interpret – evidence and answerAssumption of Equal Dispersion for Dependent Variable Groups - QuestionAssumption of Equal Dispersion for Dependent Variable Groups – Evidence and AnswerAssumption of Equal Dispersion for Dependent Variable Groups – What if Test FailedMulticollinearity - questionMulticollinearity – evidence and answerOverall relationship - questionOverall relationship – evidence and answerRelationship of functions to groups - questionRelationship of functions to groups – evidence and answerBest subset of predictors - questionBest subset of predictors – evidence and answer which predictors to interpretBest subset of predictors – evidence and answer test of statistical significanceRelationship of first independent variable - questionRelationship of first independent variable – evidence and answer: order of entryRelationship of first independent variable – evidence and answer: loadings on functionsRelationship of first independent variable – evidence and answer: comparison of meansRelationship of second independent variable - questionRelationship of second independent variable – evidence and answer: order of entryRelationship of second independent variable – evidence and answer: loadings on functionsRelationship of second independent variable – evidence and answer: comparison of meansRelationship of third independent variable - questionRelationship of third independent variable – evidence and answer: order of entryRelationship of third independent variable – evidence and answer: loadings on functionsRelationship of third independent variable – evidence and answer: comparison of meansRelationship of fourth independent variable - questionRelationship of fourth independent variable – evidence and answer: order of entryClassification accuracy - questionClassification accuracy – evidence and answer: by chance accuracy rateClassification accuracy – evidence and answer: classification accuracyValidation of discriminant model - questionValidation of discriminant model – evidence and answerAnalysis summary - questionAnalysis summary – evidence and answerSlide 93Complete discriminant analysis: level of measurementComplete discriminant analysis: sample size requirements - 1Complete discriminant analysis: sample size requirements - 2Complete discriminant analysis: assumption of normalityComplete discriminant analysis: detection of outliersComplete discriminant analysis: Model selected for interpretationComplete discriminant analysis: Assumption of equal dispersionComplete discriminant analysis: multicollinearityComplete discriminant analysis: 8Complete discriminant analysis: groups differentiated by functionsComplete discriminant analysis: individual relationships - 1Complete discriminant analysis: individual relationships - 2Complete discriminant analysis: classification accuracyComplete discriminant analysis: validationComplete discriminant analysis: summary of findings - 1Complete discriminant analysis: summary of findings - 2Discriminant Analysis Homework Problems Complete Analysis - 1Discriminant Analysis Homework Problems Complete Analysis - 2Discriminant Analysis Homework Problems Complete Analysis - 3Discriminant Analysis Homework Problems Complete Analysis - 4Discriminant Analysis Homework Problems Complete Analysis - 5Discriminant Analysis Homework Problems Complete Analysis – 6Discriminant Analysis Homework Problems Complete Analysis – 7Discriminant Analysis Homework Problems Complete Analysis – 8Discriminant Analysis Homework Problems Complete Analysis – 9Discriminant Analysis Homework Problems Complete Analysis – 10Discriminant Analysis Homework Problems Complete Analysis - 11Discriminant Analysis Homework Problems Complete Analysis - 12Discriminant Analysis Homework Problems Complete Analysis - 13Discriminant Analysis Homework Problems Complete Analysis - 14Discriminant Analysis Homework Problems Complete Analysis - 15Discriminant Analysis Homework Problems Complete Analysis - 16SW388R7Data Analysis & Computers IISlide 1Strategy for Complete Discriminant AnalysisAssumption of normality, linearity, and homogeneityOutliersMulticollinearityValidationSample problemSteps in solving problemsHomework problemsSW388R7Data Analysis & Computers IISlide 2Assumptions of normality, linearity, and homogeneity of varianceThe ability of