This edition, like previous editions, is written for those who use, rather than develop, advanced statistical methods. The focus is on conceptual understanding rather than proving results. The narrative and many examples are there to promote understanding, and a chapter on matrix algebra is included for those who need the extra help. Through- out the book, you will find output from SPSS (ve…
The auditing environment continues to change in dramatic ways, and university graduates entering the profession must be prepared for a high standard of responsibility. Here are only three examples of these changes: ● ● ● The American Institute of Certified Public Accountants (AICPA) and the International Auditing and Assurance Standards Board (IAASB) have issued clarifications tha…
Multivariate analysis techniques are popular because they enable organizations to create knowledge and thereby improve their decision making. Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or objects under investigation. Thus, any simultaneous analysis of more than two variables can be loosely considered multivariat…
academics, industry, government, and individuals are confronted with an explosion of data. The data increasingly are emerging from sources such as web traffic, social networking interactions, search behavior, sensors that track suppliers, customers, and shipments, and GPS systems that monitor traffic, to name only some of the more visible sources. This trend, often referred to as the age o…
We are delighted to present Jonas Tritschler's dissertation on Audit Quality. Auditing remains a very active research area in financial economics and account- ing. Much of the research focuses on audit quality, materiality, error rates, audit partner tenure, and auditor experience. Although there has been a convergence of thought among regulators and enforcement agencies on characteristics …
The statistical science has seen new paradigms and more complex and richer data sets. These include data on human genomics, social networks, huge climate and weather data, and, of course, high frequency financial and economic data.
The fourth edition of this book on Applied Multivariate Statistical Analysis offers a new sub-chapter on Variable Selection by using least absolute shrinkage and selection operator (LASSO) and its general form the so-called Elastic Net.
The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features. 1. A new Chapter 8 on Regression Models has been added. 2. Almost all numerical examples have been reproduced in MATLAB or R. The chapter on regression models focuses on a core business of multivariate statistical analysis. This contribution has not been subject of a prominent dis…