Multivariate Data Analysis Introduction to SPSS Outliers Normality Test of Linearity Data Transformation Bootstrapping Homoscedasticity Introduction to IBM SPSS - AMOS Multivariate Analysis of Variance (MANOVA) One Way Manova in SPSS Multiple Regression Analysis Binary Logistic Regression Factor Analysis Exploratory Factor Analysis Confirmatory Factor Analysis Cluster Analysis K - Mean Cluster Analysis Hierarchical Cluster Analysis Discriminant Analysis Correspondence Analysis Multidimensional Scaling Example - Multidimensional Scaling (ALSCAL) Neural Network Decision Trees Path Analysis Structural Equation Modeling Canonical Correlation
The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field.
"This is an ideal text for advanced undergraduate and graduate courses across the social sciences. Practitioners who need to refresh their knowledge of MDA will also find this an invaluable resource."--BOOK JACKET.
For graduate and upper-level undergraduate marketing research courses.For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.
Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications.
We first find the convex hull of the data (i.e., the observations defining the convex hull) using the following R code: R> (hull with(USairpollution, ...
Turk, M.A., 22, 704 Uitdenbogerd, A., 476, 704 Ultsch, A., 435, 704 Uthumsamy, R., 16, 679 Valdivia-Granda, W.A., 43, ... 36, 705 Williams, C.K.I., 613, 629, 705 Williams, R.J., 365 Williams, W.T., 420, 692 Wilson, R., 146, 680 Wishart, ...
Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation.
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis.
This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms.