The premise for this unique approach is that business initiatives should drive technology choices. Every discussion first addresses the business needs and then addresses the technology that supports those needs. This text provides the foundation that will enable students to achieve excellence in business, whether they major in operations management, manufacturing, sales, marketing, finance, human resources, accounting, or virtually any other business discipline. Business Driven Information Systems is designed to give students the ability to understand how information technology can be a point of strength for an organization.

    Written by authors who are highly regarded in the field, the text provides sound methodological development. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems. Statistics for Business and Economics, 9e offers proven accuracy that has led instructors to adopt it simply for its superior examples and exercises alone.

    Offering an approach with a visual/graphical emphasis, this text offers a number of examples on the premise that students learn best by doing. This book features an emphasis on interpretation of results and critical thinking over calculations.

    In a practice Hilton pioneered in the first edition, each chapter is written around a realistic business or focus company that guides the reader through the topics of that chapter. Known for balanced examples of Service, Retail, Nonprofit and Manufacturing companies, Hilton offers a clear, engaging writing style that has been praised by instructors and students alike. As in previous editions, there is significant coverage of contemporary topics such as activity-based costing, target costing, the value chain, customer profitability analysis, and throughput costing while also including traditional topics such as job-order costing, budgeting and performance evaluation.

    of Wisconsin-Madison) and Wichern (Texas A&M U.) present the newest edition of this college text on the statistical methods for describing and analyzing multivariate data, designed for students who have taken two or more statistics courses. The fifth edition includes the addition of seve

    An interesting and reader friendly writing style makes for a clear presentation, complete with all the necessary assumptions and mathematical details. Chapter topics include probability concepts and applications, decision models and decision trees, regression models, forecasting, inventory control models, linear programming modeling applications and computer analyses, network models, project management, simulation modeling, and more. For an introduction toquantitative analysis, quantitative management, operations research, or management science-especially for those individuals preparing for work in agricultural economics and health care fields.

    The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition places more emphasis on conceptual understanding and understanding results. This edition also features increased emphasis on Excel, MINITAB, and the TI-83 Plus and TI 84-Plus graphing calculators, computing technologies commonly used in such courses.

    This text is highly regarded because of its engaging and understandable introduction to statistics. The author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.

    The book focuses on the concepts of statistics with applications to the functional areas of business. It is rich in applications from accounting, finance, marketing, management and economics, covering data collection, tables and charts, probability, estimation, and more. For professionals, particularly managers, making financial analyses and decisions.

    What's new in the Second Edition? 1. Fully compliant with the latest version of SPSS version 12 2. More coverage of advanced statistics including completely new coverage of non-parametric statistics. The book is 50 per cent longer than the First Edition. 3. Each section of each chapter now has a notation - 1,2 or 3 - referring to the intended level of study. This helps students navigate their way through the book and makes it user-friendly for students of ALL levels. 4. Has a 'how to use this book' section at the start of the text. 5. Characters in each chapter have defined roles - summarizing key points, to pose questions etc 6. Each chapter now has several examples for students to work through. Answers provided on the enclosed CD-ROM

    The success of the first five editions of Global Business Today has been based in part upon the incorporation of leading edge research into the text, the use of the up-to-date examples and statistics to illustrate global trends and enterprise strategy, and the discussion of current events within the context of the appropriate theory. Our research has shown that students and instructors alike enjoy the interesting, informative, and accessible writing style of GBT - so much so that the writing has become Charles Hill's trademark. In addition to boxed material which provides deep illustrations in every chapter, Hill carefully weaves interesting anecdotes into the narrative of the text to engage the reader.

    We consistently look to the experts - full-time faculty members, adjunct instructors, and of course students - to drive the decisions we make about the text itself and the ancillary package. Through a series of focus groups, symposia, as well as full-book, single-chapter, revised manuscript reviews of both text and key ancillaries, we have heard the stories of more than 500 professors and their insights and experiences are evident on every page of the revision and in every supplement. As teachers of the course and users of their own materials, the author team is dedicated to the principles of excellence in business education. pedagogy that puts students in touch with today's real business issues, to creating groundbreaking and market-defining ancillary items for professors and students alike, Understanding Business leads the way.

    Integrated central case studies woven throughout each chapter, use real-life stories to give you a tangible and engaging framework around which to learn and understand the science behind environmental issues. Printed on FSC (Forest Stewardship Council) certified paper, the newly revised Fourth Edition engages you through the addition of new EnvisionIt photo essays.

    It is also updated to reflect the latest in theory, research, real-world examples, and use of technology. The seamless, integrated ancillary package - done by the authors - is a hallmark of this package that makes the subject more accessible for learners.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.