Multivariate Data Analysis with ReadingsDesigned for the non-statistician, this applications-oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used, while focusing instead on the fundamental concepts that affect the use of specific techniques. The fourth edition features an applicable six-step framework for each chapter, alongside revisited examples throughout. research design and data analysis courses taught in marketing, management and business departments. |
Contents
Some Basic Concepts of Multivariate Analysis | 6 |
Types of Multivariate Techniques | 13 |
Databases | 27 |
Copyright | |
17 other sections not shown
Common terms and phrases
approach assess assumptions attributes calculated canonical correlation canonical correlation analysis canonical functions canonical variate centroids channel Chapter characteristics classification cluster analysis coefficient conjoint analysis consumers correspondence analysis covariates criterion dependent determine dimensions discriminant analysis discriminant function discussed distance effect eigenvalue error estimation evaluate examine example factor analysis factor loadings factor scores firms group means HATCO holdout sample identify impact independent variables indicate individual interpretation intrachannel conflict Journal of Marketing leadership behavior linear MANOVA Marketing Research measures methods metric missing data multicollinearity multidimensional scaling multiple discriminant analysis multiple regression multivariate analysis multivariate techniques nonmetric objects observations outliers overall percent perceptual map prediction predictor variables preference procedure rebuy regression analysis relationship represent respondents rotation sample sizes selected set of variables similar solution specific Stage statistical significance structure Table tion Type I error univariate Usage Level validity versus weights X3 Price flexibility