Statistics for Business and Economics 11th Edition, Anderson

Statistics for Business and Economics 11th Edition by David R. Anderson, Dennis J. Sweeney and Thomas A. Williams provides sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information informs decisions in the business world.

Thoroughly updated, the text's more than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. And, to give you the most relevant text you can get for your course, you select the topics you want, including coverage of popular commercial statistical software programs like Minitab® 16 and Excel® 2010, along with StatTools® and other leading Excel® 2010 statistical add-ins.

This text helps students understand statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how statistics are used within business today to solve problems. Students first develop a computational foundation and learn the use of techniques before moving to statistical application and interpretation of the value of techniques.

Methods Exercises at the end of each section stress computation and use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems. Expanded, strengthened coverage of Microsoft® Office Excel® 2007 and Minitab 15 is still presented in chapter appendices to give you the flexibility of using this software or omitting this coverage as you teach. The book's Student CD provides time-saving data files and tools to efficiently complete text exercises.

The Student CD also includes appendices that address Excel 2003 and Minitab 14 with data sets for those who continue to use these earlier versions of the software. To more effectively prepare today's students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today's statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.

This book emphasizes the use of p-values as the preferred approach to hypothesis testing. To further clarify the introduction of this concept for students, the authors now separate a simplified conceptual definition of p-values from operational definitions that clarify how the p-value is computed for a lower-tail test, an upper-tail test, and a two-tail test.