1 / 9

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”

teva
Télécharger la présentation

MULTIVARIATE STATISTICS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related