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