Advanced and Multivariate Statistical Methods: Practical Application and Interpretation
- ISBN-10
- 1351971662
- ISBN-13
- 9781351971669
- Category
- Psychology
- Pages
- 390
- Language
- English
- Published
- 2016-10-24
- Publisher
- Routledge
- Authors
- Craig A. Mertler, Rachel A. Vannatta
Description
Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.
Get the book
Other editions
-
- 2021-11-30
- 324 pages
- Paperback
- Routledge
-
- 2021-11-30
- 350 pages
- Paperback
- Routledge
-
- 2016-10-24
- 391 pages
- Paperback
- Taylor & Francis
Similar books
-
Advanced Multivariate Statistics with Matrices
By Tõnu Kollo, D. von RosenThe Laplace Distribution and Generalizations. A Revisit with Applications to Communications, Economics, Engineering, and Finance. Birkhäuser, Boston. Kotz, S., Nadarajah, S. (2004). Multivariate t Distributions and Their Applications.
-
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
By Alan J. IzenmanTurk, 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, ...
-
Multivariate Statistical Methods: Going Beyond the Linear
By György TerdikThis book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations.
-
Multivariate Statistical Methods: A First Course
By George A. Marcoulides, Scott L. HershbergerA Akaike, H., 248, 308 Allen, D. A., 113, 308 Andrews, D. F., 139, 308 Arminger, G., 213, 309 B Baker, R., 68, ... 309 Flamholtz, E. (3., 68, 309 Flury, B., 253, 309 Fusilier, M, R., 158, 309 G Ganstel', D. C., 158, 309 Gibson, (1., 68, ...
-
Applied Multivariate Statistical Concepts
By Debbie L. Hahs-Vaughn... (6) part and partial correlations, (7) collinearity diagnostics, (8) Durbin-Watson, and (9) Casewise diagnostics. For this example, we apply an alpha level of .05, thus we will leave the default confidence interval percentage at 95.
-
Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM’s SPSS, Sixth Edition
By Keenan A. Pituch, James P. StevensFeatures new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers ...
-
Multivariate Statistical Methods: A Primer, Fourth Edition
By Bryan F.J. Manly, Jorge A. Navarro AlbertoThe major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies.
-
Multivariate Statistical Analysis: A Conceptual Introduction
By Sam Kash KachiganThis classic book provides the much needed conceptual explanations of advanced computer-based multivariate data analysis techniques: correlation and regression analysis, factor analysis, discrimination analysis, cluster analysis, multi-dimensional scaling, perceptual mapping,...
-
An Introduction to Applied Multivariate Analysis with R
By Brian Everitt, Torsten HothornWe 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, ...
-
A First Course in Multivariate Statistics
By Bernard FluryTwo chapters on discrimination and classification, including logistic regression, form the core of the book, followed by methods of testing hypotheses developed from heuristic principles, likelihood ratio tests and permutation tests.