Applied Statistics in Business and Economics ISE

Chapter 1: Overview of Statistics 2

Chapter 2: Data Collection 24

Chapter 3: Describing Data Visually 56

Chapter 4: Descriptive Statistics 100

Chapter 5: Probability 158

Chapter 6: Discrete Probability Distributions 200

Chapter 7: Continuous Probability Distributions 238

Chapter 8: Sampling Distributions and Estimation 278

Chapter 9: One-Sample Hypothesis Tests 322

Chapter 10: Two-Sample Hypothesis Tests 370

Chapter 11: Analysis of Variance 416

Chapter 12: Simple Regression 462

Chapter 13: Multiple Regression 522

Chapter 14: Time-Series Analysis 578

Chapter 15: Chi-Square Tests 624

Chapter 16: Nonparametric Tests 662

Chapter 17: Quality Management 692

Chapter 18: Simulation 18-1

Appendix A: Binomial Probabilities 734

Appendix B: Poisson Probabilities 736

Appendix C-1: Standard Normal Areas 739

Appendix C-2: Cumulative Standard Normal Distribution 740

Appendix D: Student’s t Critical Values 742

Appendix E: Chi-Square Critical Values 743

Appendix F: Critical Values of F.10 744

Appendix G: Solutions to Odd-Numbered Exercises 752

Appendix H: Answers to Exam Review Questions 779

Appendix I: Writing and Presenting Reports 781

Appendix J: Statistics in Excel and R 785

Appendix K:  Using Rand RStudio 789

Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how.  The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics.  It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.