ISE Business Statistics: Communicating with Numbers

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 econometrics applied to a wide range of business disciplines. Dr. Jaggia has published several papers in leading academic journals and has co-authored two successful textbooks in business statistics. 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 two successful textbooks in business statistics. Her courses in applied statistics and econometrics are well received by students as well as working professionals. 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