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: IntroductionCHAPTER 1: Data and Data PreparationPART TWO: Descriptive StatisticsCHAPTER 2: Tabular and Graphical MethodsCHAPER 3: Numerical Descriptive MeasuresPART THREE: Probability and Probability DistributionsCHAPTER 4: Introduction to ProbabilityCHAPTER 5: Discrete Probability DistributionsCHAPTER 6: Continuous Probability DistributionsPART FOUR: Basic InferenceCHAPTER 7: Sampling and Sampling DistributionsCHAPTER 8: Interval EstimationCHAPTER 9: Hypothesis TestingCHAPTER 10: Statistical Inference Concerning Two PopulationsCHAPTER 11: Statistical Inference Concerning VarianceCHAPTER 12: Chi-Square TestsPART FIVE: Advanced InferenceCHAPTER 13: Analysis of VarianceCHAPTER 14: Regression AnalysisCHAPTER 15: Inference with Regression ModelsCHAPTER 16: Regression Models for Nonlinear RelationshipsCHAPTER 17: Regression Models with Dummy VariablesPART SIX: Supplementary TopicsCHAPTER 18: Forecasting with Time Series DataCHAPTER 19: Returns, Index Numbers, and InflationCHAPTER 20: Nonparametric TestsAPPENDIX A: Getting Started with RAPPENDIX B: TablesAPPENDIX C: Answers to Selected Even-Numbered Exercises

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: IntroductionCHAPTER 1: Data and Data PreparationPART TWO: Descriptive StatisticsCHAPTER 2: Tabular and Graphical MethodsCHAPER 3: Numerical Descriptive MeasuresPART THREE: Probability and Probability DistributionsCHAPTER 4: Introduction to ProbabilityCHAPTER 5: Discrete Probability DistributionsCHAPTER 6: Continuous Probability DistributionsPART FOUR: Basic InferenceCHAPTER 7: Sampling and Sampling DistributionsCHAPTER 8: Interval EstimationCHAPTER 9: Hypothesis TestingCHAPTER 10: Statistical Inference Concerning Two PopulationsCHAPTER 11: Statistical Inference Concerning VarianceCHAPTER 12: Chi-Square TestsPART FIVE: Advanced InferenceCHAPTER 13: Analysis of VarianceCHAPTER 14: Regression AnalysisCHAPTER 15: Inference with Regression ModelsCHAPTER 16: Regression Models for Nonlinear RelationshipsCHAPTER 17: Regression Models with Dummy VariablesPART SIX: Supplementary TopicsCHAPTER 18: Forecasting with Time Series DataCHAPTER 19: Returns, Index Numbers, and InflationCHAPTER 20: Nonparametric TestsAPPENDIX A: Getting Started with RAPPENDIX B: TablesAPPENDIX C: Answers to Selected Even-Numbered Exercises

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: IntroductionCHAPTER 1: Data and Data PreparationPART TWO: Descriptive StatisticsCHAPTER 2: Tabular and Graphical MethodsCHAPER 3: Numerical Descriptive MeasuresPART THREE: Probability and Probability DistributionsCHAPTER 4: Introduction to ProbabilityCHAPTER 5: Discrete Probability DistributionsCHAPTER 6: Continuous Probability DistributionsPART FOUR: Basic InferenceCHAPTER 7: Sampling and Sampling DistributionsCHAPTER 8: Interval EstimationCHAPTER 9: Hypothesis TestingCHAPTER 10: Statistical Inference Concerning Two PopulationsCHAPTER 11: Statistical Inference Concerning VarianceCHAPTER 12: Chi-Square TestsPART FIVE: Advanced InferenceCHAPTER 13: Analysis of VarianceCHAPTER 14: Regression AnalysisCHAPTER 15: Inference with Regression ModelsCHAPTER 16: Regression Models for Nonlinear RelationshipsCHAPTER 17: Regression Models with Dummy VariablesPART SIX: Supplementary TopicsCHAPTER 18: Forecasting with Time Series DataCHAPTER 19: Returns, Index Numbers, and InflationCHAPTER 20: Nonparametric TestsAPPENDIX A: Getting Started with RAPPENDIX B: TablesAPPENDIX C: Answers to Selected Even-Numbered Exercises