
Business Statistics: Communicating with Numbers ISE
McGraw-Hill Education (Publisher)
4th Edition
Will be published approx. on 23. March 2021
Book
Paperback/Softback
1600 pages
978-1-260-59756-1 (ISBN)
Description
Business Statistics strengthens the connection between the study of business statistics and the study of business analytics. The authors believe that the 4th edition will not only prepare students in basic statistics but will also get them ready and excited about further exploration of data analytics. This edition is available for use with McGraw Hill Connect (R), a reliable, easy-to-use homework and learning management solution that embeds learning science and award-winning adaptive tools for better student results.
More details
Edition
4th edition
Language
English
Place of publication
OH
United States
Target group
College/higher education
US School Grade: From College Freshman to College Graduate Student
Illustrations
223 Illustrations
Dimensions
Height: 272 mm
Width: 198 mm
Thickness: 31 mm
Weight
1320 gr
ISBN-13
978-1-260-59756-1 (9781260597561)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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 (R)). 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 (R)). 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.
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 (R)). 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.
Content
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
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