Introduction 1 Part I: Getting Started with Business Statistics 5 Chapter 1: The Art and Science of Business Statistics 7 Chapter 2: Pictures Tell the Story: Graphical Representations of Data 23 Chapter 3: Finding a Happy Medium: Identifying the Center of a Data Set 39 Chapter 4: Searching High and Low: Measuring Variation in a Data Set 55 Chapter 5: Measuring How Data Sets Are Related to Each Other 71 Part II: Probability Theory and Probability Distributions 91 Chapter 6: Probability Theory: Measuring the Likelihood of Events 93 Chapter 7: Probability Distributions and Random Variables 111 Chapter 8: The Binomial, Geometric, and Poisson Distributions 121 Chapter 9: The Uniform and Normal Distributions: So Many Possibilities! 139 Chapter 10: Sampling Techniques and Distributions 165 Part III: Drawing Conclusions from Samples 185 Chapter 11: Confidence Intervals and the Student?s t-Distribution 187 Chapter 12: Testing Hypotheses about the Population Mean 201 Chapter 13: Testing Hypotheses about Multiple Population Means 233 Chapter 14: Testing Hypotheses about the Population Mean 251 Part IV: More Advanced Techniques: Regression Analysis and Forecasting 281 Chapter 15: Simple Regression Analysis 283 Chapter 16: Multiple Regression Analysis: Two or More Independent Variables 309 Chapter 17: Forecasting Techniques: Looking into the Future 327 Part V: The Part of Tens 351 Chapter 18: Ten Common Errors That Arise in Statistical Analysis 353 Chapter 19: Ten Key Categories of Formulas for Business Statistics 361 Index 373
Alan Anderson , PhD is a teacher of finance, economics, statistics, and math at Fordham and Fairfield universities as well as at Manhattanville and Purchase colleges. Outside of the academic environment he has many years of experience working as an economist, risk manager, and fixed income analyst. Alan received his PhD in economics from Fordham University, and an M.S. in financial engineering from Polytechnic University.