- 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
- 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
- 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)
- 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)
- 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)
- 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
- 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 Proportion
- 7.5 Determining the Sample Size
- 7.6 Confidence Interval for a Population Variance (Optional)
- 8.1 The Elements of a Test of Hypothesis
- 8.2 Formulating Hypotheses and Setting Up the Rejection Region
- 8.3 Observed Significance Levels: p-Values
- 8.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic
- 8.5 Test of Hypothesis about a Population Mean: Student's t-Statistic
- 8.6 Large-Sample Test of Hypothesis about a Population Proportion
- 8.7 Calculating Type II Error Probabilities: More about β (Optional)
- 8.8 Test of Hypothesis about a Population Variance (Optional)
- 9.1 Identifying the Target Parameter
- 9.2 Comparing Two Population Means: Independent Sampling
- 9.3 Comparing Two Population Means: Paired Difference Experiments
- 9.4 Comparing Two Population Proportions: Independent Sampling
- 9.5 Determining the Sample Size
- 9.6 Comparing Two Population Variances: Independent Sampling (Optional)
- 10.1 Elements of a Designed Study
- 10.2 The Completely Randomized Design: Single Factor
- 10.3 Multiple Comparisons of Means
- 10.4 The Randomized Block Design
- 10.5 Factorial Experiments: Two Factors
- 11.1 Probabilistic Models
- 11.2 Fitting the Model: The Least Squares Approach
- 11.3 Model Assumptions
- 11.4 Assessing the Utility of the Model: Making Inferences about the Slope β1
- 11.5 The Coefficients of Correlation and Determination
- 11.6 Using the Model for Estimation and Prediction
- 11.7 A Complete Example
- 12.1 Multiple-Regression Models
- PART I: First-Order Models with Quantitative Independent Variables
- 12.2 Estimating and Making Inferences about the β Parameters
- 12.3 Evaluating Overall Model Utility
- 12.4 Using the Model for Estimation and Prediction
- PART II: Model Building in Multiple Regression
- 12.5 Interaction Models
- 12.6 Quadratic and Other Higher Order Models
- 12.7 Qualitative (Dummy) Variable Models
- 12.8 Models with Both Quantitative and Qualitative Variables (Optional)
- 12.9 Comparing Nested Models (Optional)
- 12.10 Stepwise Regression (Optional)
- PART III: Multiple Regression Diagnostics
- 12.11 Residual Analysis: Checking the Regression Assumptions
- 12.12 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
- 13.1 Categorical Data and the Multinomial Experiment
- 13.2 Testing Categorical Probabilities: One-Way Table
- 13.3 Testing Categorical Probabilities: Two-Way (Contingency) Table
- 13.4 A Word of Caution about Chi-Square Tests
- 14.1 Introduction: Distribution-Free Tests
- 14.2 Single-Population Inferences
- 14.3 Comparing Two Populations: Independent Samples
- 14.4 Comparing Two Populations: Paired Difference Experiment
- 14.5 Comparing Three or More Populations: Completely Randomized Design
- 14.6 Comparing Three or More Populations: Randomized Block Design
- 14.7 Rank Correlation
- A. Summation Notation
- B. Tables
- C. Calculation Formulas for Analysis of Variance
- Short Answers to Selected Odd-Numbered Exercises Index
- UPDATED - The print book for the 13th Edition has been reprinted with updated statistical software screenshots. These updates help students stay on the right track when using the most current software.
- Student support is provided for learning to solve problems and for 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 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 and included in MyLab Statistics. 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 multiple parts:
- Understanding the Principles: Where applicable, these exercises help students see the big picture and encourage critical thinking while reinforcing general statistical concepts.
- Learning the Mechanics: These exercises allow students to test their ability to comprehend a mathematical concept or a definition.
- 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.
- 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 encourage students to consider the importance of ethical behavior when collecting, analyzing, 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 MyLab Statistics, so instructors can focus less time on teaching how to use the software and more time teaching and interpreting statistics.
- 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.
- Using Technology boxes at the end of each chapter offer statistical software tutorials, with step-by-step instructions and screenshots for MINITAB and, where appropriate, the TI-83/84 Plus Graphing Calculator.
- To complement the text, support for the statistical software is available in MyStatLab’s Technology Instruction Videos and the three-hole punched, tri-fold Technology Study Cards. Student discounts on select statistical software packages are also available. Ask your Pearson representative for details.
- Flexibility in coverage:
- 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, this updated edition of Statistics 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.
- 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 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.
- Additional online resources include files for text examples, exercises, Statistics in Action and Real-World case data sets marked with a data set icon. All data files are available in three formats: SAS, MINITAB, and SPSS. 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). These are available from the Pearson Math & Stats Resources site.
- 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.
Also available with MyLab Statistics
MyLab™ Statistics is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch® integrated web-based statistical software, students learn the skills they need to interact with data in the real world. For Statistics, 13th Edition, a new MyLab Revision is available that increases coverage of the end-of-section exercises throughout the book, and adds 22 brand-new, author created videos that further explore section topics and real-world case studies. Learn more about MyLab Statistics.
- NEW - Personal Inventory Assessments are a collection of online exercises designed to promote self-reflection and engagement in students. These 33 assessments include topics such as a Stress Management Assessment, Diagnosing Poor Performance and Enhancing Motivation, and Time Management Assessment.
- The print book for the 13th Edition has been reprinted with updated statistical software screenshots.
- 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.
- Continued emphasis on Ethics: where appropriate, in-text boxes emphasize the importance of ethical behavior when collecting, analyzing, and interpreting data with statistics.
Also available with MyLab Statistics
MyLab™ Statistics is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch® integrated web-based statistical software, students learn the skills they need to interact with data in the real world. For Statistics, 13th Edition, a new MyLab Revision is available that increases coverage of the end-of-section exercises throughout the book, and adds 22 brand-new, author created videos that further explore section topics and real-world case studies. Learn more about MyLab Statistics.
- New Personal Inventory Assessments are a collection of online exercises designed to promote self-reflection and engagement in students. These 33 assessments include topics such as a Stress Management Assessment, Diagnosing Poor Performance and Enhancing Motivation, and Time Management Assessment.
Produktdetaljer
Biografisk notat
Dr. Jim McClave is currently President and CEO of Info Tech, Inc., a statistical consulting and software development firm with an international clientele. He is also currently an Adjunct Professor of Statistics at the University of Florida, where he was a full-time member of the faculty for twenty years.
Dr. Terry Sincich obtained his PhD in Statistics from the University of Florida in 1980. He is an Associate Professor in the Information Systems & Decision Sciences Department at the University of South Florida in Tampa. Dr. Sincich is responsible for teaching basic statistics to all undergraduates, as well as advanced statistics to all doctoral candidates, in the College of Business Administration. He has published articles in such journals as the Journal of the American Statistical Association, International Journal of Forecasting, Academy of Management Journal, and Auditing: A Journal of Practice & Theory. Dr. Sincich is a co-author of the texts Statistics, Statistics for Business & Economics, Statistics for Engineering & the Sciences, and A Second Course in Statistics: Regression Analysis.