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MULTIVARIATE STATISTICS

MULTIVARIATE STATISTICS. Previous statistics: Crosstabs (chi-square) t-test (means) Analysis Of Variance (ANOVA) Pearson’s correlation coefficient Regression Multiple regression. Next couple of statistics:. used less frequently (bottom of your “tool box”) more “exploratory”

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MULTIVARIATE STATISTICS

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  1. MULTIVARIATE STATISTICS Previous statistics: • Crosstabs (chi-square) • t-test (means) • Analysis Of Variance (ANOVA) • Pearson’s correlation coefficient • Regression • Multiple regression Marketing Research

  2. Next couple of statistics: • used less frequently • (bottom of your “tool box”) • more “exploratory” 1. Discriminant analysis 2. Factor analysis 3. Cluster analysis Marketing Research

  3. 1. Discriminant analysis • Tests for covariation between: • Categorical dependent variable • “group” such as purchaser, non purchaser; • regular, occasional, and infrequent purchasers; • people who like “chick” flicks, those that like “guy flicks,” those that like both • Continuous and categorical IVs • age, income, gender, etc. Marketing Research

  4. 1. Discriminant analysis (continued) • which variables “group” people? • coefficients reveal importance of factors • larger coefficient, more important • smaller coefficient, less important • p-value associated with specific variables • overall fit assessed by “% correctly classified” Marketing Research

  5. 2. Factor analysis • examines covariation between: • several different variables • that are “reduced” to one or more underlying “factors” or “constructs” • e.g., overall “intelligence,” “need to consume,” etc. • often used to develop scales of related questions -- “data reduction” • no information on what causes what Marketing Research

  6. 2. Factor analysis (continued) • attempts to identify the most shared variation • the first factor is the largest amount of “variance” • the second factor is the second largest variance, etc. • Number of “factors” • “Eigenvalues” > 1.0 (“chance”) • “bend in the “Scree plot” Marketing Research

  7. 3. Cluster analysis • Covariation among a number of variables • Identifies “segments” of the sample • Used frequently in marketing • Helpful for targeting products and messages Marketing Research

  8. 4. Multi-Dimensional Scaling • abbreviated “MDS” • Subject rate “distances” or differences between objects • Data are subjected to analysis • Analysis reveal underlying “dimensions” • Used to identify how people differentiate products Marketing Research

  9. The End Marketing Research

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