Alan Anderson, PhD, FRM, is a lecturer in the department of Economics at Fordham University. He is also Adjunct Professor of Finance at NYU, Adjunct Professor of Economics and Mathematics at Purchase College, SUNY, and Adjunct Professor of Finance at Manhattanville College. He has also worked at corporate institutions such as TIAA-CREF and Reuters in quantitative risk and analyzing credit spreads.

• Introduction 1Part 1: Getting Started with Business Statistics 5Chapter 1: The Art and Science of Business Statistics 7Chapter 2: Pictures Tell the Story: Graphical Representations of Data 21Chapter 3: Identifying the Center of a Data Set 35Chapter 4: Measuring Variation in a Data Set 53Chapter 5: Measuring How Data Sets Are Related to Each Other 71Part 2: Probability Theory and Probability Distributions 95Chapter 6: Probability Theory: Measuring the Likelihood of Events 97Chapter 7: Probability Distributions and Random Variables 115Chapter 8: The Binomial and Poisson Distributions 127Chapter 9: The Normal Distribution: So Many Possibilities! 145Chapter 10: Sampling Techniques and Distributions 165Part 3: Drawing Conclusions from Samples 185Chapter 11: Confidence Intervals and the Student’s t-Distribution 187Chapter 12: Testing Hypotheses about the Population Mean 205Chapter 13: Applications of the Chi-Square Distribution 245Chapter 14: Applications of the F-Distribution 273Part 4: More Advanced Techniques: Regression Analysis and Spreadsheet Modeling 287Chapter 15: Simple Regression Analysis 289Chapter 16: Key Statistical Techniques in Excel 317Part 5: The Part of Tens 343Chapter 17: Ten Common Errors That Arise in Statistical Analysis 345Chapter 18: (Almost) Ten Key Categories of Formulas for Business Statistics 353Index 363

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Alan Anderson, PhD, FRM, is a lecturer in the department of Economics at Fordham University. He is also Adjunct Professor of Finance at NYU, Adjunct Professor of Economics and Mathematics at Purchase College, SUNY, and Adjunct Professor of Finance at Manhattanville College. He has also worked at corporate institutions such as TIAA-CREF and Reuters in quantitative risk and analyzing credit spreads.

• Introduction 1Part 1: Getting Started with Business Statistics 5Chapter 1: The Art and Science of Business Statistics 7Chapter 2: Pictures Tell the Story: Graphical Representations of Data 21Chapter 3: Identifying the Center of a Data Set 35Chapter 4: Measuring Variation in a Data Set 53Chapter 5: Measuring How Data Sets Are Related to Each Other 71Part 2: Probability Theory and Probability Distributions 95Chapter 6: Probability Theory: Measuring the Likelihood of Events 97Chapter 7: Probability Distributions and Random Variables 115Chapter 8: The Binomial and Poisson Distributions 127Chapter 9: The Normal Distribution: So Many Possibilities! 145Chapter 10: Sampling Techniques and Distributions 165Part 3: Drawing Conclusions from Samples 185Chapter 11: Confidence Intervals and the Student’s t-Distribution 187Chapter 12: Testing Hypotheses about the Population Mean 205Chapter 13: Applications of the Chi-Square Distribution 245Chapter 14: Applications of the F-Distribution 273Part 4: More Advanced Techniques: Regression Analysis and Spreadsheet Modeling 287Chapter 15: Simple Regression Analysis 289Chapter 16: Key Statistical Techniques in Excel 317Part 5: The Part of Tens 343Chapter 17: Ten Common Errors That Arise in Statistical Analysis 345Chapter 18: (Almost) Ten Key Categories of Formulas for Business Statistics 353Index 363

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Alan Anderson, PhD, FRM, is a lecturer in the department of Economics at Fordham University. He is also Adjunct Professor of Finance at NYU, Adjunct Professor of Economics and Mathematics at Purchase College, SUNY, and Adjunct Professor of Finance at Manhattanville College. He has also worked at corporate institutions such as TIAA-CREF and Reuters in quantitative risk and analyzing credit spreads.

• Introduction 1Part 1: Getting Started with Business Statistics 5Chapter 1: The Art and Science of Business Statistics 7Chapter 2: Pictures Tell the Story: Graphical Representations of Data 21Chapter 3: Identifying the Center of a Data Set 35Chapter 4: Measuring Variation in a Data Set 53Chapter 5: Measuring How Data Sets Are Related to Each Other 71Part 2: Probability Theory and Probability Distributions 95Chapter 6: Probability Theory: Measuring the Likelihood of Events 97Chapter 7: Probability Distributions and Random Variables 115Chapter 8: The Binomial and Poisson Distributions 127Chapter 9: The Normal Distribution: So Many Possibilities! 145Chapter 10: Sampling Techniques and Distributions 165Part 3: Drawing Conclusions from Samples 185Chapter 11: Confidence Intervals and the Student’s t-Distribution 187Chapter 12: Testing Hypotheses about the Population Mean 205Chapter 13: Applications of the Chi-Square Distribution 245Chapter 14: Applications of the F-Distribution 273Part 4: More Advanced Techniques: Regression Analysis and Spreadsheet Modeling 287Chapter 15: Simple Regression Analysis 289Chapter 16: Key Statistical Techniques in Excel 317Part 5: The Part of Tens 343Chapter 17: Ten Common Errors That Arise in Statistical Analysis 345Chapter 18: (Almost) Ten Key Categories of Formulas for Business Statistics 353Index 363

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