BOOK
Statistics for Business and Economics, Global Edition
James T. McClave | P. George Benson | Terry Sincich
(2018)
Additional Information
Book Details
Abstract
For courses in Introductory Business Statistics.
Real Data. Real Decisions. Real Business.
Now in its 13th Edition, Statistics for Business and Economics introduces statistics in the context of contemporary business. Emphasizing statistical literacy in thinking, the text applies its concepts with real data and uses technology to develop a deeper conceptual understanding. Examples, activities, and case studies foster active learning in the classroom while emphasizing intuitive concepts of probability and teaching students to make informed business decisions. The 13th Edition continues to highlight the importance of ethical behavior in collecting, interpreting, and reporting on data, while also providing a wealth of new and updated exercises and case studies.
Pearson MyLabTM Statistics not included. Students, if MyLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyLab should only be purchased when required by an instructor. Instructors, contact your Pearson rep for more information.
MyLab is an online homework, tutorial, and assessment platform designed 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.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Cover | Cover | ||
| Title Page | 5 | ||
| Copyright Page | 6 | ||
| Contents | 7 | ||
| Preface | 13 | ||
| Acknowledgments | 17 | ||
| 1. Statistics, Data, and Statistical Thinking | 25 | ||
| 1.1. The Science of Statistics | 27 | ||
| 1.2. Types of Statistical Applications in Business | 28 | ||
| 1.3. Fundamental Elements of Statistics | 30 | ||
| 1.4. Processes (Optional) | 34 | ||
| 1.5. Types of Data | 37 | ||
| 1.6. Collecting Data: Sampling and Related Issues | 38 | ||
| 1.7. Business Analytics: Critical Thinking with Statistics | 45 | ||
| Statistics in Action: A 20/20 View of Surveys: Fact or Fiction? | 25 | ||
| Activity 1.1: Keep the Change: Collecting Data | 54 | ||
| Activity 1.2: Identifying Misleading Statistics | 54 | ||
| Using Technology: Accessing and Listing Data; Random Sampling | 55 | ||
| 2. Methods for Describing Sets of Data | 63 | ||
| 2.1. Describing Qualitative Data | 65 | ||
| 2.2. Graphical Methods for Describing Quantitative Data | 75 | ||
| 2.3. Numerical Measures of Central Tendency | 87 | ||
| 2.4. Numerical Measures of Variability | 98 | ||
| 2.5. Using the Mean and Standard Deviation to Describe Data | 105 | ||
| 2.6. Numerical Measures of Relative Standing | 113 | ||
| 2.7. Methods for Detecting Outliers: Box Plots and z-Scores | 118 | ||
| 2.8. Graphing Bivariate Relationships (Optional) | 128 | ||
| 2.9. The Time Series Plot (Optional) | 133 | ||
| 2.10. Distorting the Truth with Descriptive Techniques | 135 | ||
| Statistics in Action: Can Money Buy Love? | 63 | ||
| Activity 2.1: Real Estate Sales | 148 | ||
| Activity 2.2: Keep the Change: Measures of Central Tendency and Variability | 148 | ||
| Using Technology: Describing Data | 149 | ||
| Making Business Decisions: The Kentucky Milk Case—Part I (Covers Chapters 1 and 2) | 154 | ||
| 3. Probability | 156 | ||
| 3.1. Events, Sample Spaces, and Probability | 158 | ||
| 3.2. Unions and Intersections | 172 | ||
| 3.3. Complementary Events | 175 | ||
| 3.4. The Additive Rule and Mutually Exclusive Events | 177 | ||
| 3.5. Conditional Probability | 184 | ||
| 3.6. The Multiplicative Rule and Independent Events | 187 | ||
| 3.7. Bayes’s Rule | 197 | ||
| Statistics in Action: Lotto Buster! | 156 | ||
| Activity 3.1: Exit Polls: Conditional Probability | 210 | ||
| Activity 3.2: Keep the Change: Independent Events | 210 | ||
| Using Technology: Combinations and Permutations | 211 | ||
| 4. Random Variables and Probability Distributions | 213 | ||
| 4.1. Two Types of Random Variables | 214 | ||
| Part I: Discrete Random Variables | 217 | ||
| 4.2. Probability Distributions for Discrete Random Variables | 217 | ||
| 4.3. The Binomial Distribution | 228 | ||
| 4.4. Other Discrete Distributions: Poisson and Hypergeometric | 241 | ||
| Part II: Continuous Random Variables | 248 | ||
| 4.5. Probability Distributions for Continuous Random Variables | 248 | ||
| 4.6. The Normal Distribution | 249 | ||
| 4.7. Descriptive Methods for Assessing Normality | 266 | ||
| 4.8. Other Continuous Distributions: Uniform and Exponential | 271 | ||
| Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold? | 213 | ||
| Activity 4.1: Warehouse Club Memberships: Exploring a Binomial Random Variable | 287 | ||
| Activity 4.2: Identifying the Type of Probability Distribution | 288 | ||
| Using Technology: Discrete Probabilities, Continuous Probabilities, and Normal Probability Plots | 289 | ||
| 5. Sampling Distributions | 295 | ||
| 5.1. The Concept of a Sampling Distribution | 297 | ||
| 5.2. Properties of Sampling Distributions: Unbiasedness and Minimum Variance | 303 | ||
| 5.3. The Sampling Distribution of the Sample Mean and the Central Limit Theorem | 307 | ||
| 5.4. The Sampling Distribution of the Sample Proportion | 316 | ||
| Statistics in Action: The Insomnia Pill: Is It Effective? | 295 | ||
| Activity 5.1: Simulating a Sampling Distribution—Cell Phone Usage | 325 | ||
| Using Technology: Simulating a Sampling Distribution | 326 | ||
| Making Business Decisions: The Furniture Fire Case (Covers Chapters 3–5) | 328 | ||
| 6. Inferences Based on a Single Sample: Estimation with Confidence Intervals | 330 | ||
| 6.1. Identifying and Estimating the Target Parameter | 332 | ||
| 6.2. Confidence Interval for a Population Mean: Normal (z) Statistic | 333 | ||
| 6.3. Confidence Interval for a Population Mean: Student’s t-Statistic | 341 | ||
| 6.4. Large-Sample Confidence Interval for a Population Proportion | 351 | ||
| 6.5. Determining the Sample Size | 358 | ||
| 6.6. Finite Population Correction for Simple Random Sampling (Optional) | 365 | ||
| 6.7. Confidence Interval for a Population Variance (Optional) | 368 | ||
| Statistics in Action: Medicare Fraud Investigations | 330 | ||
| Activity 6.1: Conducting a Pilot Study | 380 | ||
| Using Technology: Confidence Intervals | 380 | ||
| 7. Inferences Based on a Single Sample: Tests of Hypotheses | 387 | ||
| 7.1. The Elements of a Test of Hypothesis | 388 | ||
| 7.2. Formulating Hypotheses and Setting Up the Rejection Region | 393 | ||
| 7.3. Observed Significance Levels: p-Values | 399 | ||
| 7.4. Test of Hypothesis About a Population Mean: Normal (z) Statistic | 403 | ||
| 7.5. Test of Hypothesis About a Population Mean: Student’s t-Statistic | 412 | ||
| 7.6. Large-Sample Test of Hypothesis About a Population Proportion | 419 | ||
| 7.7. Test of Hypothesis About a Population Variance | 427 | ||
| 7.8. Calculating Type II Error Probabilities: More About b (Optional) | 432 | ||
| Statistics in Action: Diary of a Kleenex® User—How Many Tissues in a Box? | 387 | ||
| Activity 7.1: Challenging a Company’s Claim: Tests of Hypotheses | 446 | ||
| Activity 7.2: Keep the Change: Tests of Hypotheses | 446 | ||
| Using Technology: Tests of Hypotheses | 447 | ||
| 8. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses | 452 | ||
| 8.1. Identifying the Target Parameter | 453 | ||
| 8.2. Comparing Two Population Means: Independent Sampling | 454 | ||
| 8.3. Comparing Two Population Means: Paired Difference Experiments | 471 | ||
| 8.4. Comparing Two Population Proportions: Independent Sampling | 482 | ||
| 8.5. Determining the Required Sample Size | 490 | ||
| 8.6. Comparing Two Population Variances: Independent Sampling | 494 | ||
| Statistics in Action: ZixIt Corp. v. Visa USA Inc.—A Libel Case | 452 | ||
| Activity 8.1: Box Office Receipts: Comparing Population Means | 511 | ||
| Activity 8.2: Keep the Change: Inferences Based on Two Samples | 511 | ||
| Using Technology: Two-Sample Inferences | 512 | ||
| Making Business Decisions: The Kentucky Milk Case—Part II (Covers Chapters 6–8) | 521 | ||
| 9. Design of Experiments and Analysis of Variance | 522 | ||
| 9.1. Elements of a Designed Experiment | 524 | ||
| 9.2. The Completely Randomized Design: Single Factor | 530 | ||
| 9.3. Multiple Comparisons of Means | 547 | ||
| 9.4. The Randomized Block Design | 554 | ||
| 9.5. Factorial Experiments: Two Factors | 568 | ||
| Statistics in Action: Tax Compliance Behavior—Factors That Affect Your Level of Risk Taking When Filing Your Federal Tax Return | 522 | ||
| Activity 9.1: Designed vs. Observational Experiments | 594 | ||
| Using Technology: Analysis of Variance | 595 | ||
| 10. Categorical Data Analysis | 599 | ||
| 10.1. Categorical Data and the Multinomial Experiment | 600 | ||
| 10.2. Testing Category Probabilities: One-Way Table | 602 | ||
| 10.3. Testing Category Probabilities: Two-Way (Contingency) Table | 608 | ||
| 10.4. A Word of Caution About Chi-Square Tests | 625 | ||
| Statistics in Action: The Illegal Transplant Tissue Trade—Who Is Responsible for Paying Damages? | 599 | ||
| Activity 10.1: Binomial vs. Multinomial Experiments | 632 | ||
| Activity 10.2: Contingency Tables | 632 | ||
| Using Technology: Chi-Square Analyses | 633 | ||
| Making Business Decisions: Discrimination in the Workplace (Covers Chapters 9–10) | 637 | ||
| 11. Simple Linear Regression | 640 | ||
| 11.1. Probabilistic Models | 642 | ||
| 11.2. Fitting the Model: The Least Squares Approach | 646 | ||
| 11.3. Model Assumptions | 658 | ||
| 11.4. Assessing the Utility of the Model: Making Inferences About the Slope b1 | 663 | ||
| 11.5. The Coefficients of Correlation and Determination | 671 | ||
| 11.6. Using the Model for Estimation and Prediction | 681 | ||
| 11.7. A Complete Example | 690 | ||
| Statistics in Action: Legal Advertising—Does It Pay? | 640 | ||
| Activity 11.1: Applying Simple Linear Regression to Your Favorite Data | 703 | ||
| Using Technology: Simple Linear Regression | 704 | ||
| 12. Multiple Regression and Model Building | 708 | ||
| 12.1. Multiple Regression Models | 709 | ||
| Part I: First-Order Models with Quantitative Independent Variables | 711 | ||
| 12.2. Estimating and Making Inferences About the b Parameters | 711 | ||
| 12.3. Evaluating Overall Model Utility | 717 | ||
| 12.4. Using the Model for Estimation and Prediction | 728 | ||
| Part II: Model Building in Multiple Regression | 734 | ||
| 12.5. Interaction Models | 734 | ||
| 12.6. Quadratic and Other Higher-Order Models | 741 | ||
| 12.7. Qualitative (Dummy) Variable Models | 751 | ||
| 12.8. Models with Both Quantitative and Qualitative Variables | 758 | ||
| 12.9. Comparing Nested Models | 767 | ||
| 12.10. Stepwise Regression | 775 | ||
| Part III: Multiple Regression Diagnostics | 783 | ||
| 12.11. Residual Analysis: Checking the Regression Assumptions | 783 | ||
| 12.12. Some Pitfalls: Estimability, Multicollinearity, and Extrapolation | 797 | ||
| Statistics in Action: Bid Rigging in the Highway Construction Industry | 708 | ||
| Activity 12.1: Insurance Premiums: Collecting Data for Several Variables | 817 | ||
| Activity 12.2: Collecting Data and Fitting a Multiple Regression Model | 818 | ||
| Using Technology: Multiple Regression | 818 | ||
| Making Business Decisions: The Condo Sales Case (Covers Chapters 11–12) | 823 | ||
| Appendix A: Summation Notation | 825 | ||
| Appendix B: Basic Counting Rules | 827 | ||
| Appendix C: Calculation Formulas for Analysis of Variance | 830 | ||
| C.1. Formulas for the Calculations in the Completely Randomized Design | 830 | ||
| C.2. Formulas for the Calculations in the Randomized Block Design | 831 | ||
| C.3. Formulas for the Calculations for a Two-Factor Factorial Experiment | 832 | ||
| C.4. Tukey’s Multiple Comparisons Procedure (Equal Sample Sizes) | 833 | ||
| C.5. Bonferroni Multiple Comparisons Procedure (Pairwise Comparisons) | 834 | ||
| C.6. Scheffé’s Multiple Comparisons Procedure (Pairwise Comparisons) | 834 | ||
| Appendix D: Tables | 835 | ||
| Table I: Binomial Probabilities | 836 | ||
| Table II: Normal Curve Areas | 839 | ||
| Table III: Critical Values of t | 840 | ||
| Table IV: Critical Values of x2 | 841 | ||
| Table V: Percentage Points of the F-Distribution, a = .10 | 843 | ||
| Table VI: Percentage Points of the F-Distribution, a = .05 | 845 | ||
| Table VII: Percentage Points of the F-Distribution, a = .025 | 847 | ||
| Table VIII: Percentage Points of the F-Distribution, a = .01 | 849 | ||
| Table IX: Control Chart Constants | 851 | ||
| Table X: Critical Values for the Durbin-Watson d-Statistic, a = .05 | 852 | ||
| Table XI: Critical Values for the Durbin-Watson d-Statistic, a = .01 | 853 | ||
| Table XII: Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples | 854 | ||
| Table XIII: Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test | 855 | ||
| Table XIV: Critical Values of Spearman’s Rank Correlation Coefficient | 856 | ||
| Table XV: Critical Values of the Studentized Range, a = .05 | 857 | ||
| Answers to Selected Exercises | 859 | ||
| Selected Formulas | 871 | ||
| Index | 875 | ||
| Photo Credits | 887 | ||
| Back Cover | Back Cover |