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A First Course in Statistics, Global Edition, 12th Edition

James T. McClave
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A First Course in Statistics, Global Edition, 12th Edition

By James T. McClave, Terry T. Sincich
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Overview
Author
James T. McClave
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Edition
12th
ISBN
9781292165417
Published Date
21/11/2017
Pages
648

For courses in introductory statistics.

A Contemporary Classic

Classic, yet contemporary; theoretical, yet applied--McClave & Sincich’s A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasises inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises.

Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

Features
  • McClave and Sincich provide support to students when they are learning to solve problems and when they are studying and reviewing the material.
    • 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.
    • Examples foster problem-solving skills by taking a three-step approach: (1) "Problem", (2) "Solution", and (3) "Look Back" (or "Look Ahead"). This step-by-step process provides students with a defined structure by which to approach problems and enhances their problem-solving skills.
    • 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.
    • 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.
    • End-of-chapter 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 1,000 exercises are included, based on a wide variety of applications in various disciplines and research areas, and more than 30% 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:
    • Learning the Mechanics: These exercises allow students to test their ability to comprehend a mathematical concept or a definition.
    • Applying the ConceptsBasic: 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 analyse real-world problems.
    • Applying the Concepts–Intermediate: Based on more detailed real-world applications, these exercises require students to apply their knowledge of the technique presented in the section.
    • Applying the Concepts–Advanced: These more difficult real-data exercises require students to use critical thinking skills.
    • Critical Thinking Challenges: Students apply critical thinking skills to solve one or two challenging real-life problems. These expose students to real-world 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.
    • Ethics Boxes have been added where appropriate to highlight the importance of ethical behavior when collecting, analysing, and interpreting statistical data.
    • Statistics in Action begins each chapter with a case study based on an actual contemporary, controversial, or high-profile 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.
    • 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.
  • 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
  • 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 one-chapter coverage of simple linear regression (Chapter 11), a two-chapter 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 real-world problems
Table of contents
  • 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
  • 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)