**Summary: ** "This edition represents a significant improvement and modernization of a text which was already the best of its kind. The authors have done a wonderful job, particularly with integrating a computerized statistical tool. I commend them." Michael L. Donnell, George Washington University

"I always felt comfortable with the examples used in the textbook because they are usually real-life data. . . .The Tenth Edition brought a welcome cha ...show morenge by adding a few 'feel-at-home' type of problems, which help students' understanding of the concepts they are about to learn at first. This is a great idea. I believe in using examples whose contents are familiar (easy to understand) to students so that they can relate themselves to the problem at hand. . . . I would adopt the textbook upon completion." Yukiko Niiro, Gettysburg College

This new edition has been expanded using state-of-the-art MINITAB graphics to reflect current trends in descriptive data analysis. Much of the text has been rewritten in response to student requests to make the language and style more readable and user friendly. This classic now features a more graphic approach to modernize it, and more emphasis on the uses of the computer in statistics is also a focus for this edition. Inference making, crystal-clear explanations, and well-honed exercises with raw data sets continue to be the hallmarks for the book. Authors Bill Mendenhall and Bob Beaver are joined by Barbara Beaver as coauthor for this revision. In keeping with the evolution of statistics as a discipline and the technology it now utilizes, the authors use the computational and graphical shortcuts provided by the computer to allow more time for a discussion of statistical reasoning and the interpretation of results. They have retained the statistical accuracy and integrity of this classical text, while providing students with the most innovative techniques available as we approach the millennium.

- An increase in the use of computer-generated graphics and a simplification of explanations make the material even more accessible.
- A new Chapter 3 describes bivariate data. The chapter introduces correlation coefficient and the regression line as descriptive tools for bivariate data. The placement of this chapter makes a smooth transition from univariate to bivariate data for instructors who choose to cover this topic.
- The Analysis of Variance chapter now precedes the chapters on regression analysis. This allows the authors to include the Analysis of Variance for a regression analysis in their discussion. This chapter now include an introduction to factorial experiments.
- In the chapters on Analysis of Variance, linear formulas are presented in the main text body along with computer printouts rather than at the ends of chapters. Residual plots and their use in checking model assumptions receive more emphasis in these chapters.
- Sections at the ends of chapters called "About MINITAB" include instructions for generating MINITAB output with discussions that refer to visual screen captures from MINITAB 12 for Windows. They guide students through a "mini-lab", demonstrating the use of MINITAB for the key statistical techniques presented in that chapter.
- Each chapter shows and interprets MINITAB output and graphs.
- A new section, "Key Concepts and Formulas," concludes each chapter as appropriate. They are useful for students as a quick review for exams.
- The concept of statistical significance and p-values for a statistical test of hypothesis is presented at the outset of Chapter 10 and receives more emphasis throughout the discussion. This allows the student to use p-values interchangeably with the critical value approach to testing throughout the remainder of the text.
- Exercises include more raw data sets with a greater emphasis on the interpretation of results. More exercises are included that require written analytical responses from the students.
- Packaged with each copy of the text is a CD-ROM for the student that includes the PowerPoint lecture presentation that is provided to instructors, a tutorial program that offers practice exercises with immediate feedback, a simulation component, and the data sets for the problems in the text.
- The framework of statistical inference as the objective of statistics is now enhanced with graphics and computer usage.
- An accurate, clear execution of explanations, examples, and excercises provide a solid learning experience.
- Examples and exercises using real data sets help students learn how to analyze and present the results of statistical surveys and experiments.

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