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Statistical Analysis of Management Data

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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 third 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, this edition includes:

·         A new chapter on the analysis of mediation and moderation effects

·         Examples using STATA for most of the statistical methods

·         Example of XLSTAT applications

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 particularly relevant and typically used in management research, and to learn how they can be applied using widely available statistical software.

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A First Course in Mathematical Modeling
A First Course in Mathematical Modeling

Offering a solid introduction to the entire modeling process, A FIRST COURSE IN MATHEMATICAL MODELING, 5th Edition delivers an excellent balance of theory and practice, and gives you relevant, hands-on experience developing and sharpening your modeling skills. Throughout, the book emphasizes key facets of modeling, including creative and...

Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst
Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst

Learn the art and science of predictive analytics — techniques that get results

Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best...

Data-Intensive Computing: Architectures, Algorithms, and Applications
Data-Intensive Computing: Architectures, Algorithms, and Applications

The world is awash with digital data from social networks, blogs, business, science, and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms, and hardware, data-intensive applications can provide timely and...


An Introduction to the Mathematics of Finance, Second Edition: A Deterministic Approach
An Introduction to the Mathematics of Finance, Second Edition: A Deterministic Approach

An Introduction to the Mathematics of Finance: A Deterministic Approach, 2e, offers a highly illustrated introduction to mathematical finance, with a special emphasis on interest rates. This revision of the McCutcheon-Scott classic follows the core subjects covered by the first professional exam required of UK actuaries,...

Applied Mathematics for Science and Engineering
Applied Mathematics for Science and Engineering

Prepare students for success in using applied mathematics for engineering practice and post-graduate studies

• moves from one mathematical method to the next sustaining reader interest and easing the application of the techniques
• Uses different examples from chemical, civil, mechanical and various
...

Data Mining: The Textbook
Data Mining: The Textbook

This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences,...

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