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Managerial statistics: a case-based approach

Author: Klibanoff, Peter ; Sandroni, Alvaro ; Moselle, Boaz ; Saraniti, BrettPublisher: South-Western College Publishing, 2006.Language: EnglishDescription: 236 p. : Graphs/Ill. ; 26 cm.ISBN: 9780324314465Type of document: BookBibliography/Index: Includes indexContents Note: 1 CD included inside back cover ; 1 leaflet included: "Harvard Business School cases to accompany managerial statistics: a case based approach"
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Item type Current location Collection Call number Status Date due Barcode Item holds
Book Europe Campus
Main Collection
Print HA29 .K55 2006
(Browse shelf)
001250466
Available 001250466
Total holds: 0

Includes index

1 CD included inside back cover ; 1 leaflet included: "Harvard Business School cases to accompany managerial statistics: a case based approach"

Digitized

Managerial Statistics: A Case-Base Approach Contents Preface ix About the Authors xviii CHAPTER 1 Double E (EE) 1.1 EE: Uncertainty and Probability Probability Distribution 1.2 The Mean 1.3 The Variance and Standard Deviation The Mean and Variance of Financial Securities Standard Deviation 1.4 Proportions 1.5 The Normal Distribution Excel Functions The Standard Normal Excel Functions 1.6 The t-Distribution Excel Functions 1.7 Estimating with Data Estimating the Mean Computation of the Sample Mean Estimating the Standard Deviation 1.8 The Sampling Distribution How Accurate an Estimator is the Sample Mean? Estimating the Sampling Distribution of the Sample Mean Computing the Standard Error of the Mean 1.9 Confidence Intervals Summary New Terms New KStat and Excel Functions Excel New Formulas Case Exercises Problems 1 2 2 3 3 4 5 5 6 7 10 12 12 12 15 16 16 16 18 19 20 20 21 27 27 28 28 29 29 31 CHAPTER 2 Consumer Packaging 2.1 Hypothesis Testing: How to Make Your Case with Data 2.2 Test Marketing 2.3 Hypothesis Testing: A Formal Analysis One-Tailed Tests Mechanics of Tests Concerning a Population Mean Tests Concerning the Population Proportion 2.4 Consumer Packaging 34 35 37 42 43 45 46 46 2.5 Two Populations Population Proportions Note on Small Sample Sizes 2.6 Asset Returns Summary New Terms New Formulas New KStat and Excel Functions Excel Case Exercises Problems 49 51 52 54 55 56 56 58 58 58 60 CHAPTER 3 The Autorama 3.1 Introduction 3.2 Regressing Price on Income 3.3 Method of Least Squares 3.4 Predicting Spending from the Regression Equation Assumptions Warning 3.5 The Regression Model Dividing the Population by Income Level What Regression Estimates Quantifying the Sampling Error Confidence Intervals on the Regression Coefficients Hypothesis Tests on the Regression Coefficients Reading Significance in the Regression Output Overview of the Regression Output Table Summary New Terms New Formulas New KStat and Excel Functions Case Exercises Problems 64 65 66 70 72 72 74 74 75 76 76 77 78 79 80 80 81 81 81 82 82 CHAPTER 4 Betas and the Newspaper Case 4.1 Capital Budgeting and Risk Capital Budgeting and the Opportunity Cost of Capital 4.2 Estimating Betas Estimating Beta Confidence Interval for Beta 4.3 Predicting Circulation The Data Sampling Distribution of the Fitted Value Confidence Intervals with the Fitted Value Prediction Intervals and the Fitted Value Hypothesis Tests with the Fitted Value The Decision The R-Squared Statistic R-Squared and Asset Betas 85 86 86 88 89 90 92 92 94 95 96 97 98 99 100 Summary New Terms New Formulas New KStat and Excel Functions Case Exercises Problems 100 100 101 101 101 103 CASE INSERT 1 Energy Costs and Refrigerator Pricing CHAPTER 5 California Strawberries 5.1 Dummy Variables Dummy Variables: Revisiting the Packaging Case Interpreting Dummy Variables in the Regression Model The Regression A Note on our Assumptions Summary 5.2 California Strawberries Multiple Regression Analysis Including a Dummy and a Slope Dummy Variable 5.3 Head-hunting Agency Summary New Terms Case Exercises Problems 106 107 108 108 108 108 110 110 110 114 116 121 122 122 124 CHAPTER 6 Forestier Wine 6.1 Snowfall, Unemployment, and Spurious Correlation 6.2 Wine and Wealth Summary New Terms New KStat and Excel Functions Case Exercises Problems 128 129 131 145 145 145 146 147 CHAPTER 7 The Hot Dog Case 7.1 The Hot Dog Case 2 Hot Dog Case: Solutions, Multicollinearity, Hidden Extrapolation and Tests of Joint Significance 7.3 Analyzing Sums and Differences of Regression Coefficients 7.4 Detecting Multicollinearity 7.5 Omitted Variable Bias Calculating the Extent of the Bias Summary New Terms New Formulas New KStat and Excel Functions Excel Case Exercises 149 150 7. 150 158 160 162 164 166 167 167 168 168 168 CASE INSERT 2 Colonial Broadcasting CHAPTER 8 The Advertising Case 8.1 A Primer on Logarithms in Regression Properties of the Natural Logarithm Function (LN) 8.2 Logarithmic Regressions: Forms And Interpretation of the Coefficients 8.3 Prediction With Logarithmic Regressions 8.4 Ad Sales: Using Logarithmic Regressions 8.5 Introduction to Heteroskedasticity 8.6 An Optional Mathematical Digression 8.7 Heteroskedasticity: Detecting, Effect on Results, Possible Fixes New Terms New Formulas New KStat and Excel Functions Excel Case Exercises 171 172 173 173 174 176 176 178 180 181 182 183 183 183 184 CHAPTER 9 Soda Sales and Harmon Foods 9.1 Soda Sales Introduction Introducing Seasonal Dummies Interpreting the Dummy Coefficients Seasonality and Autocorrelation Summary 9.2 Seasonality: Using Seasonal Indices in Forecasting 9.3 The Harmon Foods, Inc. Case Questions to Prepare 9.4 Regression Analysis of Time Series Data Summary 9.5 Time Series Analysis Summary New Terms Case Exercises 187 188 188 189 189 191 191 191 192 193 193 195 195 198 198 199 CASE INSERT 3 Nopane Advertising Strategy CASE INSERT 4 The Baseball Case APPENDIX INDEX 201 202 210 231

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