Business Statistics: Communicating with Numbers ISE

Sanjiv Jaggia is a professor of economics and finance at California Polytechnic State University in San Luis Obispo. Dr. Jaggia holds a Ph.D. from Indiana University and is a Chartered Financial Analyst (CFA®). He enjoys research in statistics and data analytics applied to a wide range of business disciplines. Dr. Jaggia has published numerous papers in leading academic journals and has co-authored three successful textbooks, two in business statistics and one in business analytics. His ability to communicate in the classroom has been acknowledged by several teaching awards. Dr. Jaggia resides in San Luis Obispo with his wife and daughter. In his spare time, he enjoys cooking, hiking, and listening to a wide range of music.  Alison Kelly is a professor of economics at Suffolk University in Boston. Dr. Kelly holds a Ph.D. from Boston College and is a Chartered Financial Analyst (CFA®). Dr. Kelly has published in a wide variety of academic journals and has co-authored three successful textbooks, two in business statistics and one in business analytics. Her courses in applied statistics and econometrics are popular with students as well as working professionals. She has also served as a consultant for a number of companies; her most recent work focused on how large financial institutions satisfy requirements mandated by the Dodd-Frank Act. Dr. Kelly resides in Hamilton, Massachusetts, with her husband, daughter, and son. In her spare time, she enjoys exercising and gardening. 

PART ONE: Introduction





CHAPTER 1: Data and Data Preparation





PART TWO: Descriptive Statistics





CHAPTER 2: Tabular and Graphical Methods





CHAPER 3: Numerical Descriptive Measures





PART THREE: Probability and Probability Distributions





CHAPTER 4: Introduction to Probability





CHAPTER 5: Discrete Probability Distributions





CHAPTER 6: Continuous Probability Distributions





PART FOUR: Basic Inference





CHAPTER 7: Sampling and Sampling Distributions





CHAPTER 8: Interval Estimation





CHAPTER 9: Hypothesis Testing





CHAPTER 10: Statistical Inference Concerning Two Populations





CHAPTER 11: Statistical Inference Concerning Variance





CHAPTER 12: Chi-Square Tests





PART FIVE: Advanced Inference





CHAPTER 13: Analysis of Variance





CHAPTER 14: Regression Analysis





CHAPTER 15: Inference with Regression Models





CHAPTER 16: Regression Models for Nonlinear Relationships





CHAPTER 17: Regression Models with Dummy Variables





PART SIX: Supplementary Topics





CHAPTER 18: Forecasting with Time Series Data





CHAPTER 19: Returns, Index Numbers, and Inflation





CHAPTER 20: Nonparametric Tests





APPENDIX A: Getting Started with R





APPENDIX B: Tables





APPENDIX C: Answers to Selected Even-Numbered Exercises