Statistics, 13/e (IEPaperback)
James Bohan
 出版商: Pearson FT Press
 出版日期: 20180903
 售價: $1,280
 貴賓價: 9.5 折 $1,216
 語言: 英文
 頁數: 896
 裝訂: Paperback
 ISBN: 1292161558
 ISBN13: 9781292161556

相關分類:
機率統計學 Probabilityandstatistics
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商品描述
本書序言
· 25% of the 2,000+ exercises are updated or new, based on contemporary studies and real data. Most of these exercises foster and promote critical thinking skills.
· Updated technology: all printouts from statistical software (SAS, SPSS, MINITAB, and the TI83/Tl84 Plus Graphing Calculator) and corresponding instructions for use have been revised to reflect the latest versions of the software.
· New Statistics in Action Cases: six of the 14 cases are new or updated, each based on real data from a recent study.
· Continued emphasis on Ethics: where appropriate, boxes have been added emphasizing the importance of ethical behavior when collecting, analyzing, and interpreting data with statistics.
Pearson MyLab Statistics not included. Students, if Pearson MyLab Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. Pearson MyLab Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
· 25% new and updated exercises give students more of the practice they need to succeed.
· StatCrunch^{™} applets have been updated to run in HTML5, so that they are more accessible and will run on most computers and tablets without additional plugins.
· Datainformed updates: the authors have analyzed aggregated student usage and performance data from the previous edition's Pearson MyLab Statistics course. The results of this analysis helped improved the quality and quantity of exercises that matter most to instructors and students.
Content Changes
 Chapter 1 (Statistics, Data, and Statistical Thinking): Material on all basic sampling concepts (e.g., random sampling and sample survey designs) has been streamlined and moved to Section 1.5 (Collecting Data: Sampling and Related Issues).
 Chapter 2 (Methods for Describing Sets of Data): The section on summation notation has been moved to the appendix (Appendix A). Also, recent examples of misleading graphics have been added to Section 2.9 (Distorting the Truth with Descriptive Statistics).
 Chapter 4 (Discrete Random Variables) and Chapter 5 (Continuous Random Variables): Use of technology for computing probabilities of random variables with known probability distributions (e.g., binomial, Poisson, normal, and exponential distributions) has been incorporated into the relevant sections of these chapters. This reduces the use of tables of probabilities for these distributions.
 Chapter 6 (Sampling Distributions): In addition to the sampling distribution of the sample mean, we now cover (in new Section 6.4) the sampling distribution of a sample proportion.
 Chapter 8 (Inferences Based on a Single Sample: Tests of Hypothesis): The section on pvalues in hypothesis testing (Section 8.3) has been moved up to emphasize the importance of their use in reallife studies. Throughout the remainder of the text, conclusions from a test of hypothesis are based on pvalues
本書特色
· McClave and Sincich provide support to students when they are learning to solve problems and when they are studying and reviewing the material.
o “Where We’re Going” bullets begin each chapter, offering learning objectives and providing section numbers that correspond to where each concept is discussed in the chapter.
o Examples foster problemsolving skills by taking a threestep approach: (1) "Problem", (2) "Solution", and (3) "Look Back" (or "Look Ahead"). This stepbystep process provides students with a defined structure by which to approach problems and enhances their problemsolving skills.
o The "Look Back" feature gives helpful hints for solving the problem and/or provides a further reflection or insight into the concept or procedure that is covered.
o A “Now Work” exercise suggestion follows each Example, which provides a practice exercise that is similar in style and concept to the example. Students test and confirm their understanding immediately.
o Endofchapter summaries now serve as a more effective study aid for students. Important points are reinforced through flow graphs (which aid in selecting the appropriate statistical method) and boxed notes with key words, formulas, definitions, lists, and key concepts.
· More than 2,000 exercises are included, based on a wide variety of applications in various disciplines and research areas, and more than 25% have been updated for the new edition. Some students have difficulty learning the mechanics of statistical techniques while applying the techniques to real applications. For this reason, exercise sections are divided into four parts:
o Learning the Mechanics: These exercises allow students to test their ability to comprehend a mathematical concept or a definition.
o Applying the Concepts—Basic: Based on applications taken from a wide variety of journals, newspapers, and other sources, these short exercises help students begin developing the skills necessary to diagnose and analyze realworld problems.
o Applying the Concepts—Intermediate: Based on more detailed realworld applications, these exercises require students to apply their knowledge of the technique presented in the section.
o Applying the Concepts—Advanced: These more difficult realdata exercises require students to use critical thinking skills.
o Critical Thinking Challenges: Students apply critical thinking skills to solve one or two challenging reallife problems. These expose students to realworld problems with solutions that are derived from careful, logical thought and use of the appropriate statistical analysis tool.
· Case studies, applications, and biographies keep students motivated and show the relevance of statistics.
o Ethics Boxes have been added where appropriate to highlight the importance of ethical behavior when collecting, analyzing, and interpreting statistical data.
o Statistics in Action begins each chapter with a case study based on an actual contemporary, controversial, or highprofile issue. Relevant research questions and data from the study are presented and the proper analysis demonstrated in short "Statistics in Action Revisited" sections throughout the chapter.
o Brief Biographies of famous statisticians and their achievements are presented within the main chapter, as well as in marginal boxes. Students develop an appreciation for the statistician's efforts and the discipline of statistics as a whole.
· Support for statistical software is integrated throughout the text and online, so instructors can focus less time on teaching the software and more time teaching statistics.
o Each statistical analysis method presented is demonstrated using output from SAS, SPSS, and MINITAB. These outputs appear in examples and exercises, exposing students to the output they will encounter in their future careers.
o Using Technology boxes at the end of each chapter offer statistical software tutorials, with stepbystep instructions and screenshots for MINITAB and, where appropriate, the TI83/84 Plus Graphing Calculator.
o To complement the text, support for the statistical software is available in Pearson MyLab Statistics’ Technology Instruction Videos. Student discounts on select statistical software packages are also available. Ask your Pearson representative for details.
· Flexibility in Coverage
o Probability and Counting Rules:
§ Probability poses a challenge for instructors because they must decide on the level of presentation, and students find it a difficult subject to comprehend.
§ Unlike other texts that combine probability and counting rules, McClave/Sincich includes the counting rules (with examples) in an appendix rather than in the body of the chapter on probability; the instructor can control the level of coverage of probability covered.
o Multiple Regression and Model Building:
§ Two full chapters are devoted to discussing the major types of inferences that can be derived from a regression analysis, showing how these results appear in the output from statistical software, and, most important, selecting multiple regression models to be used in an analysis.
§ The instructor has the choice of a onechapter coverage of simple linear regression (Chapter 11), a twochapter treatment of simple and multiple regression (excluding the sections on model building in Chapter 12), or complete coverage of regression analysis, including model building and regression diagnostics.
§ This extensive coverage of such useful statistical tools will provide added evidence to the student of the relevance of statistics to realworld problems.
o Additional online resources include files for text examples, exercises, Statistics in Action and RealWorld case data sets marked with a data set icon. Also available is Chapter 14, Nonparametric Statistics, and a set of applets that allow students to run simulations that visually demonstrate some of the difficult statistical concepts (e.g., sampling distributions and confidence intervals).
o Role of calculus:
§ Although the text is designed for students without a calculus background, footnotes explain the role of calculus in various derivations.
§ Footnotes are also used to inform the student about some of the theory underlying certain methods of analysis. They provide additional flexibility in the mathematical and theoretical level at which the material is presented.
Pearson MyLab Statistics not included. Students, if Pearson MyLab Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. Pearson MyLab Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
作者簡介
James T. McClave, University of Florida
Terry T Sincich, University of South Florida
目錄大綱
1. Statistics, Data, and Statistical Thinking
2. Methods for Describing Sets of Data
3. Probability
4. Discrete Random Variables
5. Continuous Random Variables
6. Sampling Distributions
7. Inferences Based on a Single Sample: Estimation with Confidence Intervals
8. Inferences Based on a Single: Tests of Hypohesis
9. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses
10. Analysis of Variance: Comparing More than Two Means
11. Simple Linear Regression
12. Multiple Regression and Model Building
13. Categorical Data Analysis
14. Nonparametric Statistics (available online)
Appendices
Short Answers to Selected OddNumbered Exercises