Statistics > EXAM > Summary 1ZM31 Multivariate Data Analysis by Hair- Questions & Answers (2023) (All)

Summary 1ZM31 Multivariate Data Analysis by Hair- Questions & Answers (2023)

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Multivariate Data Analysis - -deals with statistical analysis of observations where there are multiple responses on each observational unit -a single variable - -MDA models reality where each situation, product, or decision involves more than _____ -process the information in a meaningful fashion - -Multivariate Analysis can be used to ___ -1. Consumer and market research 2. Quality control and assurance 3. Process optimization and process control 4. Research and development - -Uses of MVDA -Principle Component Analysis/Factor Analysis - -obtain a summary or an overview of a table identify the dominant patterns in the data such as groups, outliers, trends, and so on -Principal Component Analysis - -a class of procedures used for data reduction and summarization -interdependence technique - -PCA is an _____: no distinction between dependent and independent variables -1. to identify underlying dimensions, or factors, that explain the correlations among a set of variables 2. to identify a new, smaller, set of uncorrelated variables to replace the original set of correlated variables - -Uses of Factor Analysis -Bartlett's test of sphericity - -is used to test the hypothesis that the variables are uncorrelated in the population -Correlation Matrix - -is a lower triangle matrix showing the simple correlations between all possible pairs of variables included in the analysis -1 - -diagonal element are all ___ -Communality - -amount of variance a variable shares with all the other variables -Eigenvalue - -represents the total variance explained by each factor -Factor loadings - -correlations between the variables and the factors -Factor Matrix - -contains the factor loadings of all the variables on all the factors -Factor Scores - -composite scores estimated for each respondent on the derived factors -Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy - -used to examine the appropriateness of factor analysis. 0.5-1: appropriatness Below 0.5: inapproriateness -Percentage of Variance - -The percentage of total variance attributed to each factor -Scree plots - -plot of the eigenvalues against the number of factors in order of extraction -Classification and Discriminant Analysis - -analyze groups in the table, how these groups differ, and to which group individual table rows belong -Discriminant Analysis - -used to determine which variables discriminate between two or more naturally occuring groups very similar to ANOVA -Multiple Regression Analysis or Partial Least Squares - -finds relationships between columns in data tables to use one set of variables to predict another, for the purpose of optimization -

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