Название: Multivariate Data Analysis, 8th edition
Автор: Joseph F. Hair, William C. Black, Barry J. Babin
Издательство: Cengage
Год: 2019
Страниц: 834
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. The eighth edition of Multivariate Data Analysis provides an updated perspective on the 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 serves as the perfect companion for graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques.

The information available for decision making has exploded in recent years, and will continue to do so in the future, probably even faster. Until recently, much of that information just disappeared. It was either not collected or discarded. Today this information is being collected and stored in data warehouses, and it is available to be “mined” for improved decision-making. Some of that information can be analyzed and understood with simple statistics, but much of it requires more complex, multivariate statistical techniques to convert these data into knowledge.

A number of technological advances help us to apply multivariate techniques. Among the most important are the developments in computer hardware and software. The speed of computing equipment has doubled every 18 months while prices have tumbled. User-friendly software packages brought data analysis into the point-and-click era, and we can quickly analyze mountains of complex data with relative ease. Indeed, industry, government, and university-related research centers throughout the world are making widespread use of these techniques.

An expanded feature from prior editions are the software-specific resources to enable a researcher to replicate the analyses in the text in SAS, IBM SPSS, and SmartPLS for that book. In addition to these software commands, actual outputs for all of the analyses in the text are available for the student to examine and even compare to their results. The authors are also committed to continue development of these resources, hopefully extending theses supplements to include selected R code and outputs in the near future.