1. Statistics, Data, and Statistical Thinking 1.1 The Science of Statistics 1.2 Types of Statistical Applications 1.3 Fundamental Elements of Statistics 1.4 Types of Data 1.5 Collecting Data: Sampling and Related Issues 1.6 The Role of Statistics in Critical Thinking and Ethics   Statistics in Action: Social Media Network Usage—Are You Linked In?   Using Technology: MINITAB: Accessing and Listing Data   2. Methods for Describing Sets of Data 2.1 Describing Qualitative Data 2.2 Graphical Methods for Describing Quantitative Data 2.3 Numerical Measures of Central Tendency 2.4 Numerical Measures of Variability 2.5 Using the Mean and Standard Deviation to Describe Data 2.6 Numerical Measures of Relative Standing 2.7 Methods for Detecting Outliers: Box Plots and z-Scores 2.8 Graphing Bivariate Relationships (Optional) 2.9 Distorting the Truth with Descriptive Statistics   Statistics in Action: Body Image Dissatisfaction: Real or Imagined?   Using Technology: MINITAB: Describing Data TI-83/TI–84 Plus Graphing Calculator: Describing Data   3. Probability 3.1 Events, Sample Spaces, and Probability 3.2 Unions and Intersections 3.3 Complementary Events 3.4 The Additive Rule and Mutually Exclusive Events 3.5 Conditional Probability 3.6 The Multiplicative Rule and Independent Events 3.7 Some Additional Counting Rules (Optional) 3.8 Bayes’s Rule (Optional)   Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?   Using Technology: TI-83/TI-84 Plus Graphing Calculator: Combinations and Permutations   4. Discrete Random Variables 4.1 Two Types of Random Variables 4.2 Probability Distributions for Discrete Random Variables 4.3 Expected Values of Discrete Random Variables 4.4 The Binomial Random Variable 4.5 The Poisson Random Variable (Optional) 4.6 The Hypergeometric Random Variable (Optional)   Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?   Using Technology: MINITAB: Discrete Probabilities TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables and Probabilities   5. Continuous Random Variables 5.1 Continuous Probability Distributions 5.2 The Uniform Distribution 5.3 The Normal Distribution 5.4 Descriptive Methods for Assessing Normality 5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional) 5.6 The Exponential Distribution (Optional)   Statistics in Action: Super Weapons Development—Is the Hit Ratio Optimized?   Using Technology: MINITAB: Continuous Random Variable Probabilities and Normal Probability Plots TI-83/TI-84 Plus Graphing Calculator: Normal Random Variable and Normal Probability Plots   6. Sampling Distributions 6.1 The Concept of a Sampling Distribution 6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance 6.3 The Sampling Distribution of (x-bar) and the Central Limit Theorem 6.4 The Sampling Distribution of the Sample Proportion   Statistics in Action: The Insomnia Pill: Is It Effective?   Using Technology: MINITAB: Simulating a Sampling Distribution   7. Inferences Based on a Single Sample: Estimation with Confidence Intervals 7.1 Identifying and Estimating the Target Parameter 7.2 Confidence Interval for a Population Mean: Normal (z) Statistic 7.3 Confidence Interval for a Population Mean: Student’s t-Statistic 7.4 Large-Sample Confidence Interval for a Population Propo

This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content which is especially relevant to students outside the United States. About this Text · 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 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. 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 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 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 real-world problems. o 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. o Applying the Concepts—Advanced: These more difficult real-data exercises require students to use critical thinking skills. o 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. 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 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. 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 e

About the Book · 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 TI-83/Tl-84 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. · StatCrunchTM 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. · Data-informed 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 p-values in hypothesis testing (Section 8.3) has been moved up to emphasize the importance of their use in real-life studies. Throughout the remainder of the text, conclusions from a test of hypothesis are based on p-values.