Applied Statistics in Business and Economics: 2024 Release ISE

David P. Doane is Professor of Quantitative Methods in Oakland University's Department of Decision and Information Sciences. He earned his Bachelor of Arts degree in mathematics and economics at the University of Kansas and his PhD from Purdue University's Krannert Graduate School. Lori E. Seward is an Instructor in the Decisions Sciences Department in the College of Business at The University of Colorado at Denver and Health Sciences Center. She earned her Bachelor of Science and Master of Science degrees in Industrial Engineering at Virginia Tech. After several years working as a reliability and quality engineer in the paper and automotive industries, she earned her PhD from Virginia Tech.

• 1 Overview of Statistics 2 Data Collection 3 Describing Data Visually 4 Descriptive Statistics 5 Probability 6 Discrete Probability Distributions 7 Continuous Probability Distributions 8 Sampling Distributions and Estimation 9 One-Sample Hypothesis Tests 10 Two-Sample Hypothesis Tests 11 Analysis of Variance 12 Simple Regression 13 Multiple Regression 14 Time-Series Analysis 15 Chi-Square Tests 16 Nonparametric Tests 17 Quality Management 18 Simulation Appendix A: Binomial Probabilities Appendix B: Poisson Probabilities Appendix C-1: Standard Normal Areas Appendix C-2: Cumulative Standard Normal Distribution Appendix D: Student’s t Critical Values Appendix E: Chi-Square Critical Values Appendix F: Critical Values of F.10  Appendix G: Solutions to Odd-Numbered Exercises Appendix H: Answers to Exam Review Questions Appendix I: Writing and Presenting Reports Appendix J: Statistics in Excel and R Appendix K: Using R and RStudio