Business analytics : descriptive, predictive, prescriptive

✍ Scribed by Jeffrey D. Camm; (Of the University of Alabama) James J. Cochran; (Of the University of Iowa) Jeffrey W. Ohlmann; Michael J. Fry

• Year: 2021
• Tongue: English
• Leaves: 882
• Edition: Fourth
• Category: Library

✦ Table of Contents

Cover
Brief Contents
Contents
Preface
Chapter 1: Introduction
1.1 Decision Making
1.2 Business Analytics Defined
1.3 A Categorization of Analytical Methods and Models
1.4 Big Data
1.5 Business Analytics in Practice
1.6 Legal and Ethical Issues in the Use of Data and Analytics
Summary
Glossary
Chapter 2: Descriptive Statistics
2.1 Overview of Using Data: Definitions and Goals
2.2 Types of Data
2.3 Modifying Data in Excel
2.4 Creating Distributions from Data
2.5 Measures of Location
2.6 Measures of Variability
2.7 Analyzing Distributions
2.8 Measures of Association Between Two Variables
2.9 Data Cleansing
Summary
Glossary
Problems
Case Problem 1: Heavenly Chocolates Web Site Transactions
Case Problem 2: African Elephant Populations
Chapter 3: Data Visualization
3.1: Overview of Data Visualization
3.2: Tables
3.3: Charts
3.4: Advanced Data Visualization
3.5: Data Dashboards
Summary
Glossary
Problems
Case Problem 1: Pelican stores
Case Problem 2: Movie Theater Releases
Appendix: Data Visualization in Tableau
Chapter 4: P robability: An Introduction to Modeling Uncertainty
4.1 Events and Probabilities
4.2 Some Basic Relationships of Probability
4.3 Conditional Probability
4.4 Random Variables
4.5 Discrete Probability Distributions
4.6 Continuous Probability Distributions
Summary
Glossary
Problems
Case Problem 1: Hamilton County Judges
Case Problem 2: McNeil’s Auto Mall
Case Problem 3: Gebhardt Electronics
Chapter 5: Descriptive Data Mining
5.1 Cluster Analysis
5.2 Association Rules
5.3 Text Mining
Summary
Glossary
Problems
Case Problem 1: Big Ten Expansion
Case Problem 2: Know Thy Customer
Chapter 6: Statistical Inference
6.1 Selecting a Sample
6.2 Point Estimation
6.3 Sampling Distributions
6.4 Interval Estimation
6.5 Hypothesis Tests
6.6 Big Data, Statistical Inference, and Practical Significance
Summary
Glossary
Problems
Case Problem 1: Young Professional Magazine
Case Problem 2: Quality Associates, Inc.
Chapter 7: Linear Regression
7.1 Simple Linear Regression Model
7.2 Least Squares Method
7.3 Assessing the Fit of the Simple Linear Regression Model
7.4 The Multiple Regression Model
7.5 Inference and 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
Glossary
Problems
Case Problem 1: Alumni Giving
Case Problem 2: Consumer Research, Inc.
Case Problem 3: Predicting Winnings for NASCAR Drivers
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 Using Regression Analysis for Forecasting
8.5 Determining the Best Forecasting Model to Use
Summary
Glossary
Problems
Case Problem 1: Forecasting Food and Beverage Sales
Case Problem 2: Forecasting Lost Sales
Appendix: Using the Excel Forecast Sheet
Chapter 9: Predictive Data Mining
9.1 Data Sampling, Preparation, and Partitioning
9.2 Performance Measures
9.3 Logistic Regression
9.4 k-Nearest Neighbors
9.5 Classification and Regression Trees
Summary
Glossary
Problems
Case Problem: Grey Code Corporation
Chapter 10: Spreadsheet Models
10.1 Building Good Spreadsheet Models
10.2 What-If Analysis
10.3 Some Useful Excel Functions for Modeling
10.4 Auditing Spreadsheet Models
10.5 Predictive and Prescriptive Spreadsheet Models
Summary
Glossary
Problems
Case Problem: Retirement Plan
Chapter 11: Monte Carlo Simulation
11.1 Risk Analysis for Sanotronics LLC
11.2 Inventory Policy Analysis for Promus Corp
11.3 Simulation Modeling for Land Shark Inc.
11.4 Simulation with Dependent Random Variables
11.5 Simulation Considerations
Summary
Glossary
Problems
Case Problem: Four Corners
Appendix: Common Probability Distributions for Simulation
Chapter 12: Linear Optimization Models
12.1 A Simple Maximization Problem
12.2 Solving the Par, Inc. Problem
12.3 A Simple Minimization Problem
12.4 Special Cases of Linear Program Outcomes
12.5 Sensitivity Analysis
12.6 General Linear Programming Notation and More Examples
12.7 Generating an Alternative Optimal Solution for a Linear Program
Summary
Glossary
Problems
Case Problem: Investment Strategy
Chapter 13: Integer Linear Optimization Models
13.1 Types of Integer Linear Optimization Models
13.2 Eastborne Realty, an Example of Integer Optimization
13.3 Solving Integer Optimization Problems with Excel Solver
13.4 Applications Involving Binary Variables
13.5 Modeling Flexibility Provided by Binary Variables
13.6 Generating Alternatives in Binary Optimization
Summary
Glossary
Problems
Case Problem: Applecore Children’s Clothing
Chapter 14: Nonlinear Optimization Models
14.1 A Production Application: Par, Inc. Revisited
14.2 Local and Global Optima
14.3 A Location Problem
14.4 Markowitz Portfolio Model
14.5 Adoption of a New Product: The Bass Forecasting Model
Summary
Glossary
Problems
Case Problem: Portfolio Optimization with Transaction Costs
Chapter 15: Decision Analysis
15.1 Problem Formulation
15.2 Decision Analysis Without Probabilities
15.3 Decision Analysis with Probabilities
15.4 Decision Analysis with Sample Information
15.5 Computing Branch Probabilities with Bayes’ Theorem
15.6 Utility Theory
Summary
Glossary
Problems
Case Problem: Property Purchase Strategy
Multi-Chapter Case Problems
Appendix A: Basics of Excel
Appendix B Database Basics with Microsoft Access
References
Index