xix, 675 pages : 26 cm Machine generated contents note: ch. 1 Introduction -- 1.1.Decision Making -- 1.2.Business Analytics Defined -- 1.3.A Categorization of Analytical Methods and Models -- Descriptive Analytics -- Predictive Analytics -- Prescriptive Analytics -- Analytics in Action: Procter & Gamble Uses Business Analytics to Redesign its Supply Chain -- 1.4.Big Data -- 1.5.Business Analytics in Practice -- Financial Analytics -- Human Resource (HR) Analytics -- Marketing Analytics -- Health Care Analytics -- Supply Chain Analytics -- Analytics for Government and Nonprofits -- Sports Analytics -- Web Analytics -- Summary -- Glossary -- ch. 2 Descriptive Statistics -- Analytics in Action: U.S. Census Bureau -- 2.1.Overview of Using Data: Definitions and Goals -- 2.2.Types of Data -- Population and Sample Data -- Quantitative and Categorical Data -- Cross-Sectional and Time Series Data -- Sources of Data -- 2.3.Modifying Data in Excel -- Sorting and Filtering Data in Excel -- Conditional Formatting of Data in Excel -- 2.4.Creating Distributions from Data -- Frequency Distributions for Categorical Data -- Relative Frequency and Percent Frequency Distributions -- Frequency Distributions for Quantitative Data -- Histograms -- Cumulative Distributions -- 2.5.Measures of Location -- Mean (Arithmetic Mean) -- Median -- Mode -- Geometric Mean -- 2.6.Measures of Variability -- Range -- Variance -- Standard Deviation -- Coefficient of Variation -- 2.7.Analyzing Distributions -- Percentiles -- Quartiles -- z-scores -- Empirical Rule -- Identifying Outliers -- Box Plots -- 2.8.Measures of Association Between Two Variables -- Scatter Charts -- Covariance -- Correlation Coefficient -- Summary -- Glossary -- Problems -- Case: Heavenly Chocolates Web Site Transactions -- Appendix: Creating Box Plots in XLMiner -- ch. 3 Data Visualization -- Analytics in Action: Cincinnati Zoo & Botanical Garden -- 3.1.Overview of Data Visualization -- Effective Design Techniques -- 3.2.Tables -- Table Design Principles -- Crosstabulation -- PivotTables in Excel -- 3.3.Charts -- Scatter Charts -- Line Charts -- Bar Charts and Column Charts -- A Note on Pie Charts and 3-D Charts -- Bubble Charts -- Heat Maps -- Additional Charts for Multiple Variables -- PivotCharts in Excel -- 3.4.Advanced Data Visualization -- Advanced Charts -- Geographic Information Systems Charts -- 3.5.Data Dashboards -- Principles of Effective Data Dashboards -- Applications of Data Dashboards -- Summary -- Glossary -- Problems -- Case Problem: All-Time Movie Box Office Data -- Appendix: Creating a Scatter Chart Matrix and a Parallel Coordinates Plot with XLMiner -- ch. 4 Linear Regression -- Analytics in Action: Alliance Data Systems -- 4.1.The Simple Linear Regression Model -- Regression Model and Regression Equation -- Estimated Regression Equation -- 4.2.Least Squares Method -- Least Squares Estimates of the Regression Parameters -- Using Excel's Chart Tools to Compute the Estimated Regression Equation -- 4.3.Assessing the Fit of the Simple Linear Regression Model -- The Sums of Squares -- The Coefficient of Determination -- Using Excel's Chart Tools to Compute the Coefficient of Determination -- 4.4.The Multiple Regression Model -- Regression Model and Regression Equation -- Estimated Multiple Regression Equation -- Least Squares Method and Multiple Regression -- Butler Trucking Company and Multiple Regression -- Using Excel's Regression Tool to Develop the Estimated Multiple Regression Equation -- 4.5.Inference and Regression -- Conditions Necessary for Valid Inference in the Least Squares Regression Model -- Testing for an Overall Regression Relationship -- Testing Individual Regression Parameters -- Addressing Nonsignificant Independent Variables -- Multicollinearity -- Inference and Very Large Samples -- 4.6.Categorical Independent Variables -- Butler Trucking Company and Rush Hour -- Interpreting the Parameters -- More Complex Categorical Variables -- 4.7.Modeling Nonlinear Relationships -- Quadratic Regression Models -- Piecewise Linear Regression Models -- Interaction Between Independent Variables -- 4.8.Model Fitting -- Variable Selection Procedures -- Overfitting -- Summary -- Glossary -- Problems -- Case Problem: Alumni Giving -- Appendix: Using XLMiner for Regression -- ch. 5 Time Series Analysis and Forecasting -- Analytics in Action: Forecasting Demand for a Broad Line of Office Products -- 5.1.Time Series Patterns -- Horizontal Pattern -- Trend Pattern -- Seasonal Pattern -- Trend and Seasonal Pattern -- Cyclical Pattern -- Identifying Time Series Patterns -- 5.2.Forecast Accuracy -- 5.3.Moving Averages and Exponential Smoothing -- Moving Averages -- Forecast Accuracy -- Exponential Smoothing -- Forecast Accuracy -- 5.4.Using Regression Analysis for Forecasting -- Linear Trend Projection -- Seasonality -- Seasonality Without Trend -- Seasonality with Trend -- Using Regression Analysis as a Causal Forecasting Method -- Combining Causal Variables with Trend and Seasonality Effects -- Considerations in Using Regression in Forecasting -- 5.5.Determining the Best Forecasting Model to Use -- Summary -- Glossary -- Problems -- Case Problem: Forecasting Food and Beverage Sales -- Appendix: Using XLMiner for Forecasting -- ch. 6 Data Mining -- Analytics in Action: Online Retailers Using Predictive Analytics to Cater to Customers -- 6.1.Data Sampling -- 6.2.Data Preparation -- Treatment of Missing Data -- Identification of Outliers and Erroneous Data -- Variable Representation -- 6.3.Unsupervised Learning -- Cluster Analysis -- Association Rules -- 6.4.Supervised Learning -- Partitioning Data -- Classification Accuracy -- Prediction Accuracy -- k-Nearest Neighbors -- Classification and Regression Trees -- Logistic Regression -- Summary -- Glossary -- Problems -- Case Problem: Grey Code Corporation -- ch. 7 Spreadsheet Models -- Analytics in Action: Procter and Gamble Sets Inventory Targets Using Spreadsheet Models -- 7.1.Building Good Spreadsheet Models -- Influence Diagrams -- Building a Mathematical Model -- Spreadsheet Design and Implementing the Model in a Spreadsheet -- 7.2.What-If Analysis -- Data Tables -- Goal Seek -- 7.3.Some Useful Excel Functions for Modeling -- Sum and Sumproduct -- If and Countif -- Vlookup -- 7.4.Auditing Spreadsheet Models -- Trace Precedents and Dependents -- Show Formulas -- Evaluate Formulas -- Error Checking -- Watch Window -- Summary -- Glossary -- Problems -- Case Problem: Retirement Plan -- ch. 8 Linear Optimization Models -- Analytics in Action: Timber Harvesting Model at MeadWestvaco Corporation -- 8.1.A Simple Maximization Problem -- Problem Formulation -- Mathematical Model for the Par, Inc. Problem -- 8.2.Solving the Par, Inc. Problem -- The Geometry of the Par, Inc. Problem -- Solving Linear Programs with Excel Solver -- 8.3.A Simple Minimization Problem -- Problem Formulation -- Solution for the M&D Chemicals Problem -- 8.4.Special Cases of Linear Program Outcomes -- Alternative Optimal Solutions -- Infeasibility -- Unbounded -- 8.5.Sensitivity Analysis -- Interpreting Excel Solver Sensitivity Report -- 8.6.General Linear Programming Notation and More Examples -- Investment Portfolio Selection -- Transportation Planning -- Advertising Campaign Planning -- 8.7.Generating an Alternative Optimal Solution for a Linear Program -- Summary -- Glossary -- Problems -- Case Problem: Investment Strategy -- Appendix: Solving Linear Optimization Models Using Analytic Solver Platform -- ch 9 Integer Linear Optimization Models -- Analytics in Action: Optimizing the Transport of Oil Rig Crews -- 9.1.Types of Integer Linear Optimization Models -- 9.2.Eastborne Realty, An Example of Integer Optimization -- The Geometry of Linear All-Integer Optimization -- 9.3.Solving Integer Optimization Problems with Excel Solver -- A Cautionary Note About Sensitivity Analysis -- 9.4.Applications Involving Binary Variables -- Capital Budgeting -- Fixed Cost -- Bank Location -- Product Design and Market Share Optimization -- 9.5.Modeling Flexibility Provided by Binary Variables -- Multiple-Choice and Mutually Exclusive Constraints -- k out of n Alternatives Constraint -- Conditional and Corequisite Constraints -- 9.6.Generating Alternatives in Binary Optimization -- Summary -- Glossary -- Problems -- Case Problem: Applecore Children's Clothing -- Appendix: Solving Integer Linear Optimization Problems Using Analytic Solver Platform -- ch. 10 Nonlinear Optimization Models -- Analytics in Action: Intercontinental Hotels Optimizes Retail Pricing -- 10.1.A Production Application: Par, Inc. Revisited -- An Unconstrained Problem -- A Constrained Problem -- Solving Nonlinear Optimization Models Using Excel Solver -- Sensitivity Analysis and Shadow Prices in Nonlinear Models -- 10.2.Local and Global Optima -- Overcoming Local Optima with Excel Solver -- 10.3.A Location Problem -- 10.4.Markowitz Portfolio Model -- 10.5.Forecasting Adoption of a New Product -- Summary -- Glossary -- Problems -- Case Problem: Portfolio Optimization with Transaction Costs -- Appendix: Solving Nonlinear Optimization Problems with Analytic Solver Platform -- ch. 11 Monte Carlo Simulation -- Analytics in Action: Reducing Patient Infections in the ICU -- 11.1.What-If Analysis -- The Sanotronics Problem -- Base-Case Scenario -- Worst-Case Scenario -- Best-Case Scenario -- 11.2.Simulation Modeling with Native Excel Functions -- Use of Probability Distributions to Represent Random Variables -- Generating Values for Random Variables with Excel -- Executing Simulation Trials with Excel -- Measuring and Analyzing Simulation Output -- 11.3.Simulation Modeling with Analytic Solver Platform -- The Land Shark Problem -- Spreadsheet Model for Land Shark -- Generating Values for Land Shark's Random Variables -- Tracking Output Measures for Land Shark -- Executing Simulation Trials and Analyzing Output for Land Shark -- The Zappos Problem -- Spreadsheet Model for Zappos Note continued: Modeling Random Variables for Zappos -- Tracking Output Measures for Zappos -- Executing Simulation Trials and Analyzing Output for Zappos -- 11.4.Simulation Optimization -- 11.5.Simulation Considerations -- Verification and Validation -- Advantages and Disadvantages of Using Simulation -- Summary -- Glossary -- Problems -- Case Problem: Four Corners -- Appendix 11.1 Incorporating Dependence Between Random Variables -- Appendix 11.2 Probability Distributions for Random Variables -- ch. 12 Decision Analysis -- Analytics in Action: Phytopharm's New Product Research and Development -- 12.1.Problem Formulation -- Payoff Tables -- Decision Trees -- 12.2.Decision Analysis Without Probabilities -- Optimistic Approach -- Conservative Approach -- Minimax Regret Approach -- 12.3.Decision Analysis with Probabilities -- Expected Value Approach -- Risk Analysis -- Sensitivity Analysis -- 12.4.Decision Analysis with Sample Information -- Expected Value of Sample Information -- Expected Value of Perfect Information -- 12.5.Computing Branch Probabilities with Bayes' Theorem -- 12.6.Utility Theory -- Utility and Decision Analysis -- Utility Functions -- Exponential Utility Function -- Summary -- Glossary -- Problems -- Case Problem: Property Purchase Strategy -- Appendix: Using Analytic Solver Platform to Create Decision Trees