Always Learning

Advanced Search

Statistics plus MyStatLab with Pearson eText, Global Edition

Statistics plus MyStatLab with Pearson eText, Global Edition

13th Edition

James McClave, Terry Sincich

Feb 2018, Valuepack
ISBN13: 9781292161655
ISBN10: 1292161655
For orders to USA, Canada, Australia, New Zealand or Japan visit your local Pearson website
Special online offer - Save 10%
Was 70.99, Now 63.89Save: 7.10
This title is available in the following formats:
Format RRPYour Price
Valuepack £70.99 £63.89
Paperback £59.99 £59.99
  • Print pagePrint page
  • Email this pageEmail page
  • Share

For courses in introductory statistics.

This package includes MyStatLab™.

A Contemporary Classic

Classic, yet contemporary; theoretical, yet applied—McClave & Sincich’s Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes 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.

This package includes MyStatLab, an online homework, tutorial, and assessment program designed to work with this text to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

MyStatLab should only be purchased when required by an instructor. Please be sure you have the correct ISBN and Course ID. Instructors, contact your Pearson representative for more information.

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 Proportion

7.5 Determining the Sample Size

7.6 Confidence Interval for a Population Variance (Optional)

Statistics in Action: Medicare Fraud Investigations

Using Technology: MINITAB: Confidence Intervals

TI-83/TI-84 Plus Graphing Calculator: Confidence Intervals

8. Inferences Based on a Single

Sample: Tests of Hypothesis

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)

Statistics in Action: Diary of a KLEENEX® User—How Many Tissues in a Box?

Using Technology: MINITAB: Tests of Hypotheses

TI-83/TI-84 Plus Graphing Calculator: Tests of Hypotheses

9. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses

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)

Statistics in Action: ZixIt Corp. v. Visa USA Inc.—A Libel Case

Using Technology: MINITAB: Two-Sample Inferences

TI-83/TI-84 Plus Graphing Calculator: Two Sample Inferences

10. Analysis of Variance: Comparing More than Two Means

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

Statistics in Action: Voice versus Face Recognition—Does One Follow the Other?

Using Technology: MINITAB: Analysis of Variance

TI-83/TI-84 Plus Graphing Calculator: Analysis of Variance

11. Simple Linear Regression

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

Statistics in Action: Can “Dowsers” Really Detect Water?

Using Technology: MINITAB: Simple Linear Regression

TI-83/TI-84 Plus Graphing Calculator: Simple Linear Regression

12. Multiple Regression and Model Building

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

Statistics in Action: Modeling Condominium Sales: What Factors Affect

Auction Price? Using Technology: MINITAB: Multiple Regression TI-83/TI-84 Plus Graphing Calculator: Multiple Regression

13. Categorical Data Analysis

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

Statistics in Action: The Case of the Ghoulish Transplant Tissue Using Technology: MINITAB: Chi-Square Analyses TI-83/TI-84 Plus Graphing Calculator: Chi-Square Analyses

14. Nonparametric Statistics (available online)

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 14-48

Statistics in Action: Pollutants at a Housing Development: A Case of Mishandling Small Samples 14-2

Using Technology: MINITAB: Nonparametric Tests 14-65

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.
    • 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. 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 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 have been added where appropriate to highlight 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 online, so instructors can focus less time on teaching the software and more time teaching 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, 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.
    • 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).
    • 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.

This package includes MyStatLab™, an online homework, tutorial, and assessment program designed to work with this text to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

  • NEW! 25% new and updated exercises give students more of the practice they need to succeed.
  • NEW! 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.
  • NEW! Data-informed updates: the authors have analyzed aggregated student usage and performance data from the previous edition's MyStatLab course. The results of this analysis helped improved the quality and quantity of exercises that matter most to instructors and students.