Joseph F. Hai, JR. is Cleverdon Chair of Business at University of South Alabama, USA. William C. Black is Professor Emeritus in the Department of Marketing, Ourso College of Business at Louisiana State University, USA. Barr is Max P. Watson,Jr. Professor of Business at Louisiana Tech University, USA. RolphE. Anderson is the Royal H. Gibson Sr. Professor of Business Administration at Drexel University, USA.
Multivariate Data Analysis
8th edition
Par : , , , Formats :
- Paiement en ligne :
- Livraison à domicile ou en point Mondial Relay estimée à partir du 23 septembreCet article sera commandé chez un fournisseur et vous sera envoyé 127 jours après la date de votre commande.
- Retrait Click and Collect en magasin gratuit
- Réservation en ligne avec paiement en magasin :
- Indisponible pour réserver et payer en magasin
- Nombre de pages813
- FormatGrand Format
- PrésentationBroché
- Poids1.375 kg
- Dimensions19,8 cm × 26,1 cm × 3,0 cm
- ISBN978-1-4737-5654-0
- EAN9781473756540
- Date de parution24/05/2018
- ÉditeurCengage Learning
Résumé
The past decade has seen an explosion in the interest and application of data analytics in both academic research and decision-making in all types of organizations. The emergence of Big Data has provided a newfound wealth of information available to address questions in all fields of study.The eighth edition of Multivariate Data Analysis provides an updated perspective on data analysis of all types of data as well as introducing some new perspectives and techniques that are foundational in today's world of analytics.
Multivariate Data Analysis is an advanced level ceát that is suitable for students on business related degrees from final year undergraduate level up to PhD level. Key Features : New chapter on partial least squares uctural equation modeling (PLS-SEM), an emerging technique with equal applicability for researchers in the academic and organizational domains. Unique"Rule of Thumb" feature helps you to learn how to hest use different techniques.
Extended discussions of emerging topics, including causal treatments/inference (i.e., causal analysis of non-experimental data as well as propensity score models) along with multi-level and panel data models (extending regression into new research areas and providing a frathework for cross-sectional/time-series analysis). Online resources for researchers including continued coverage from past editions of all of the analyses from the latest versions of both SAS and SPSS (commands and outputs).
Multivariate Data Analysis is an advanced level ceát that is suitable for students on business related degrees from final year undergraduate level up to PhD level. Key Features : New chapter on partial least squares uctural equation modeling (PLS-SEM), an emerging technique with equal applicability for researchers in the academic and organizational domains. Unique"Rule of Thumb" feature helps you to learn how to hest use different techniques.
Extended discussions of emerging topics, including causal treatments/inference (i.e., causal analysis of non-experimental data as well as propensity score models) along with multi-level and panel data models (extending regression into new research areas and providing a frathework for cross-sectional/time-series analysis). Online resources for researchers including continued coverage from past editions of all of the analyses from the latest versions of both SAS and SPSS (commands and outputs).