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Product details:
ISBN 10: 1337406420
ISBN 13: 9781337406420
Author: Jeffrey Camm
Build valuable skills that are in high demand in today’s businesses with BUSINESS ANALYTICS, 3E. You master the full range of analytics as you strengthen your descriptive, predictive and prescriptive analytic skills. Real-world examples and visuals help illustrate data and results for each topic. Clear, step-by-step instructions for various software programs, including Microsoft Excel, Analytic Solver, and JMP Pro, teach you how to perform the analyses discussed. Practical, relevant problems at all levels of difficulty further help you apply what you’ve learned to succeed in your course.
Business Analytics 3rd Table of contents:
Chapter 1. Introduction
1.1. Decision Making
1.2. Business Analytics Defined
1.3. A Categorization of Analytical Methods and Models
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Descriptive Analytics
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Predictive Analytics
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Prescriptive Analytics
1.4. Big Data -
Volume
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Velocity
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Variety
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Veracity
1.5. Business Analytics in Practice -
Financial Analytics
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Human Resource (HR) Analytics
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Marketing Analytics
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Health Care Analytics
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Supply-Chain Analytics
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Analytics for Government and Nonprofits
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Sports Analytics
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Web Analytics
Summary
Chapter 2. Descriptive Statistics
2.1. Overview of Using Data: Definitions and Goals
2.2. Types of Data
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Population and Sample Data
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Quantitative and Categorical Data
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Cross-Sectional and Time Series Data
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Sources of Data
2.3. Modifying Data in Excel -
Sorting and Filtering Data
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Conditional Formatting
2.4. Creating Distributions from Data -
Frequency Distributions for Categorical Data
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Relative Frequency and Percent Frequency Distributions
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Frequency Distributions for Quantitative Data
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Histograms
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Cumulative Distributions
2.5. Measures of Location -
Mean (Arithmetic Mean)
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Median
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Mode
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Geometric Mean
2.6. Measures of Variability -
Range
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Variance
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Standard Deviation
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Coefficient of Variation
2.7. Analyzing Distributions -
Percentiles
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Quartiles
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z-Scores
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Empirical Rule
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Identifying Outliers
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Box Plots
2.8. Measures of Association Between Two Variables -
Scatter Charts
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Covariance
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Correlation Coefficient
2.9. Data Cleansing -
Missing Data
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Identification of Erroneous Outliers and Other Erroneous Values
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Variable Representation
Summary
Problems
Case Problem: Heavenly Chocolates Web Site Transactions
Appendix 2.1: Creating Box Plots with Analytic Solver
Chapter 3. Data Visualization
3.1. Overview of Data Visualization
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Effective Design Techniques
3.2. Tables -
Table Design Principles
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Crosstabulation
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PivotTables in Excel
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Recommended PivotTables
3.3. Charts -
Scatter Charts
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Recommended Charts
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Line Charts
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Bar Charts and Column Charts
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Pie Charts and 3D Charts
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Bubble Charts
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Heat Maps
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Additional Charts for Multiple Variables
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PivotCharts
3.4. Advanced Data Visualization -
Advanced Charts
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Geographic Information Systems Charts
3.5. Data Dashboards -
Principles of Effective Dashboards
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Applications of Dashboards
Summary
Problems
Case Problem: All-Time Movie Box-Office Data
Appendix 3.1: Creating a Scatter-Chart Matrix and Parallel-Coordinates Plot with Analytic Solver
Chapter 4. Descriptive Data Mining
4.1. Cluster Analysis
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Measuring Similarity
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Hierarchical Clustering
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k-Means Clustering
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Comparing Clustering Methods
4.2. Association Rules -
Evaluating Association Rules
4.3. Text Mining -
Preprocessing Text Data
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Applications (e.g., Voice of the Customer, Movie Reviews)
Summary
Problems
Case Problem: Know Thy Customer
Appendices 4.1–4.9: Various Techniques Using Analytic Solver and JMP Pro
Chapter 5. Probability: An Introduction to Modeling Uncertainty
5.1. Events and Probabilities
5.2. Basic Probability Relationships
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Complements
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Addition Law
5.3. Conditional Probability -
Independent Events
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Multiplication Law
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Bayes’ Theorem
5.4. Random Variables -
Discrete and Continuous
5.5. Discrete Probability Distributions -
Expected Value and Variance
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Uniform, Binomial, and Poisson Distributions
5.6. Continuous Probability Distributions -
Uniform, Triangular, Normal, Exponential Distributions
Summary
Problems
Case Problem: Hamilton County Judges
Chapter 6. Statistical Inference
6.1. Selecting a Sample
6.2. Point Estimation
6.3. Sampling Distributions
6.4. Interval Estimation
6.5. Hypothesis Testing
6.6. Big Data and Statistical Inference
Summary
Problems
Case Problems:
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Young Professional Magazine
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Quality Associates, Inc
Chapter 7. Linear Regression
7.1. Simple Linear Regression
7.2. Least Squares Method
7.3. Assessing the Fit
7.4. Multiple Regression
7.5. Inference in Regression
7.6. Categorical Independent Variables
7.7. Modeling Nonlinear Relationships
7.8. Model Fitting
7.9. Big Data and Regression
7.10. Prediction with Regression
Summary
Problems
Case Problem: Alumni Giving
Appendix 7.1: Regression with Analytic Solver
Chapter 8. Time Series Analysis and Forecasting
8.1. Time Series Patterns
8.2. Forecast Accuracy
8.3. Moving Averages and Exponential Smoothing
8.4. Regression for Forecasting
8.5. Choosing the Best Forecast Model
Summary
Problems
Case Problem: Forecasting Food and Beverage Sales
Appendices 8.1–8.2: Excel and Analytic Solver Tools
Chapter 9. Predictive Data Mining
9.1. Data Sampling and Partitioning
9.2. Performance Measures
9.3. Logistic Regression
9.4. k-Nearest Neighbors
9.5. Classification and Regression Trees
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Ensemble Methods
Summary
Problems
Case Problem: Grey Code Corporation
Appendices 9.1–9.10: Techniques in Analytic Solver and JMP Pro
Chapter 10. Spreadsheet Models
10.1. Building Good Models
10.2. What-If Analysis
10.3. Useful Excel Functions
10.4. Auditing Models
10.5. Predictive and Prescriptive Models
Summary
Problems
Case Problem: Retirement Plan
Chapter 11. Monte Carlo Simulation
11.1. Risk Analysis
11.2. Simulation Modeling
11.3. Dependent Random Variables
11.4. Simulation Considerations
Summary
Problems
Case Problem: Four Corners
Appendices 11.1–11.5: Simulation Tools with Excel and Analytic Solver
Chapter 12. Linear Optimization Models
12.1. Maximization Problem
12.2. Solving with Excel Solver
12.3. Minimization Problem
12.4. Special Cases in LP
12.5. Sensitivity Analysis
12.6. LP Notation and Examples
12.7. Generating Alternative Solutions
Summary
Problems
Case Problem: Investment Strategy
Appendix 12.1: Solving with Analytic Solver
Chapter 13. Integer Linear Optimization Models
13.1. Types of Models
13.2. Integer Optimization Example
13.3. Solving with Excel Solver
13.4. Binary Variable Applications
13.5. Modeling Flexibility
13.6. Generating Alternatives
Summary
Problems
Case Problem: Applecore Children’s Clothing
Appendix 13.1: Solving with Analytic Solver
Chapter 14. Nonlinear Optimization Models
14.1. Production Application
14.2. Local and Global Optima
14.3. Location Problem
14.4. Markowitz Portfolio Model
14.5. Product Adoption Forecasting
Summary
Problems
Case Problem: Portfolio Optimization with Transaction Costs
Appendix 14.1: Solving with Analytic Solver
Chapter 15. Decision Analysis
15.1. Problem Formulation
15.2. Decision Analysis without Probabilities
15.3. Decision Analysis with Probabilities
15.4. Sample Information in Decision Making
15.5. Bayes’ Theorem for Branch Probabilities
15.6. Utility Theory
Summary
Problems
Case Problem: Property Purchase Strategy
Appendix 15.1: Creating Decision Trees with Analytic Solver
Appendices
Appendix A. Basics of Excel
Appendix B. Database Basics with Microsoft Access
Appendix C. Solutions to Even-Numbered Questions
Appendix D. Problem Settings for JMP and Analytic Solver
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