Teaches students how to apply statistics to real business problems through the authors' unique three-step approach to problem solving. Students learn to identify, compute and interpret the results in the context of the problem.

Statistics For Management is a textbook of business statistics that helps students grasp the fundamentals of the subject in a simple and easy manner.Statistics For Management is a detailed textbook on the subject of business statistics. It seeks to dispel the seeming complexity of the subject by presenting the concepts in a lucid and visually demonstrative manner. The book begins with an overview of business statistics. Subsequent chapters cover topics like tables and graphs, probability, sampling, estimation, testing hypotheses, and quality and quality control. The last few chapters present concepts like chi-square, analysis of variance, simple regression and multiple regression, non-parametric methods, time series and forecasting, and index numbers. The book ends with a chapter on decision theory. The concepts in the book are explained at length, and illustrative explanations are given precedence over complex mathematical notations. Also, each discussion is accompanied by examples that demonstrate one or more real world applications of the concepts. All the hypothesis tests are conducted using the standardized scale. Every section ends with three types of exercises for practice self-evaluative, basic, and application exercises. A very useful feature of the book is the Hints And Assumptions feature, which provides useful hints for solving the exercise problems and alerts the students about the commonly committed mistakes while solving them. Statistics For Management was published in 2011 by Pearson.

Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on: confirmatory factor analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-group confirmatory factor analysis and analysis of covariance structures. Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software.

This is the first book to introduce senior level students of management science practicing managers to the modern powerful statistical methods that are available for optimizing and improving business processes. Using realistic case studies from businesses, this book explains the key statistical concepts workers in this field need to know. In particular, there is a focus on the use of probabilistic methods and statistical analysis in a business context and the value of these methods for managers. The mathematical explanations are comprehensive with an emphasis on the essential principles.