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Business Analytics : Data Analysis & Decision Making.

Bibliographic Details
Main Author: Albright, S. Christian.
Other Authors: Winston, Wayne L.
Format: eBook
Language:English
Published: Mason, OH : Cengage, 2020.
Edition:7th ed.
Subjects:
Microsoft Excel (Computer file).
Decision making-Computer programs..
Industrial management-Statistical methods-Computer programs.
Electronic books.
Online Access:View fulltext via EzAccess
Table of Contents:
  • Cover
  • About the Authors
  • Brief Contents
  • Contents
  • Preface
  • Chapter 1: Introduction to Business Analytics
  • 1-1 Introduction
  • 1-2 Overview of the Book
  • 1-3 Introduction to Spreadsheet Modeling
  • 1-4 Conclusion
  • Summary of Key Terms
  • Problems
  • Part 1: Data Analysis
  • Chapter 2: Describing the Distribution of a Variable
  • 2-1 Introduction
  • 2-2 Basic Concepts
  • 2-3 Summarizing Categorical Variables
  • 2-4 Summarizing Numeric Variables
  • 2-5 Time Series Data
  • 2-6 Outliers and Missing Values
  • 2-7 Excel Tables for Filtering, Sorting, and Summarizing
  • 2-8 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 2.1 Correct Interpretation of Means
  • Case 2.2 The Dow Jones Industrial Average
  • Case 2.3 Home and Condo Prices
  • Appendix: Introduction to StatTools
  • Chapter 3: Finding Relationships among Variables
  • 3-1 Introduction
  • 3-2 Relationships among Categorical Variables
  • 3-3 Relationships among Categorical Variables and a Numeric Variable
  • 3-4 Relationships among Numeric Variables
  • 3-5 Pivot Tables
  • 3-6 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 3.1 Customer Arrivals at Bank98
  • Case 3.2 Saving, Spending, and Social Climbing
  • Case 3.3 Churn in the Cellular Phone Market
  • Case 3.4 Southwest Border Apprehensions and Unemployment
  • Appendix: Using StatTools to Find Relationships
  • Chapter 4: Business Intelligence (BI) Tools for Data Analysis
  • 4-1 Introduction
  • 4-2 Importing Data into Excel with Power Query
  • 4-3 Data Analysis with Power Pivot
  • 4-4 Data Visualization with Tableau Public
  • 4-5 Data Cleansing
  • 4-6 Conclusion
  • Summary of Key Terms
  • Problems
  • Part 2: Probability and Decision Making under Uncertainty
  • Chapter 5: Probability and Probability Distributions
  • 5-1 Introduction
  • 5-2 Probability Essentials
  • 5-3 Probability Distribution of a Random Variable.
  • 5-4 The Normal Distribution
  • 5-5 The Binomial Distribution
  • 5-6 The Poisson and Exponential Distributions
  • 5-7 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 5.1 Simpson's Paradox
  • Case 5.2 EuroWatch Company
  • Case 5.3 Cashing in on the Lottery
  • Chapter 6: Decision Making under Uncertainty
  • 6-1 Introduction
  • 6-2 Elements of Decision Analysis
  • 6-3 EMV and Decision Trees
  • 6-4 One-Stage Decision Problems
  • 6-5 The PrecisionTree Add-In
  • 6-6 Multistage Decision Problems
  • 6-7 The Role of Risk Aversion
  • 6-8 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 6.1 Jogger Shoe Company
  • Case 6.2 Westhouser Paper Company
  • Case 6.3 Electronic Timing System for Olympics
  • Case 6.4 Developing a Helicopter Component for the Army
  • Appendix: Decision Trees with DADM_Tools
  • Part 3: Statistical Inference
  • Chapter 7: Sampling and Sampling Distributions
  • 7-1 Introduction
  • 7-2 Sampling Terminology
  • 7-3 Methods for Selecting Random Samples
  • 7-4 Introduction to Estimation
  • 7-5 Conclusion
  • Summary of Key Terms
  • Problems
  • Chapter 8: Confidence Interval Estimation
  • 8-1 Introduction
  • 8-2 Sampling Distributions
  • 8-3 Confidence Interval for a Mean
  • 8-4 Confidence Interval for a Total
  • 8-5 Confidence Interval for a Proportion
  • 8-6 Confidence Interval for a Standard Deviation
  • 8-7 Confidence Interval for the Difference between Means
  • 8-8 Confidence Interval for the Difference between Proportions
  • 8-9 Sample Size Selection
  • 8-10 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 8.1 Harrigan University Admissions
  • Case 8.2 Employee Retention at D&amp
  • Y
  • Case 8.3 Delivery Times at SnowPea Restaurant
  • Chapter 9: Hypothesis Testing
  • 9-1 Introduction
  • 9-2 Concepts in Hypothesis Testing
  • 9-3 Hypothesis Tests for a Population Mean
  • 9-4 Hypothesis Tests for Other Parameters.
  • 9-5 Tests for Normality
  • 9-6 Chi-Square Test for Independence
  • 9-7 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 9.1 Regression toward the Mean
  • Case 9.2 Friday Effect in the Stock Market
  • Case 9.3 Removing Vioxx from the Market
  • Part 4: Regression Analysis and Time Series Forecasting
  • Chapter 10: Regression Analysis: Estimating Relationships
  • 10-1 Introduction
  • 10-2 Scatterplots: Graphing Relationships
  • 10-3 Correlations: Indicators of Linear Relationships
  • 10-4 Simple Linear Regression
  • 10-5 Multiple Regression
  • 10-6 Modeling Possibilities
  • 10-7 Validation of the Fit
  • 10-8 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 10.1 Quantity Discounts at Firm Chair Company
  • Case 10.2 Housing Price Structure in Mid City
  • Case 10.3 Demand for French Bread at Howie's Bakery
  • Case 10.4 Investing for Retirement
  • Chapter 11: Regression Analysis: Statistical Inference
  • 11-1 Introduction
  • 11-2 The Statistical Model
  • 11-3 Inferences about the Regression Coefficients
  • 11-4 Multicollinearity
  • 11-5 Include/Exclude Decisions
  • 11-6 Stepwise Regression
  • 11-7 Outliers
  • 11-8 Violations of Regression Assumptions
  • 11-9 Prediction
  • 11-10 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 11.1 Heating Oil at Dupree Fuels
  • Case 11.2 Developing a Flexible Budget at the Gunderson Plant
  • Case 11.3 Forecasting Overhead at Wagner Printers
  • Chapter 12: Time Series Analysis and Forecasting
  • 12-1 Introduction
  • 12-2 Forecasting Methods: An Overview
  • 12-3 Testing for Randomness
  • 12-4 Regression-Based Trend Models
  • 12-5 The Random Walk Model
  • 12-6 Moving Averages Forecasts
  • 12-7 Exponential Smoothing Forecasts
  • 12-8 Seasonal Models
  • 12-9 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 12.1 Arrivals at the Credit Union
  • Case 12.2 Forecasting Weekly Sales at Amanta.
  • Appendix: Alternative Forecasting Software
  • Part 5: Optimization and Simulation Modeling
  • Chapter 13: Introduction to Optimization Modeling
  • 13-1 Introduction
  • 13-2 Introduction to Optimization
  • 13-3 A Two-Variable Product Mix Model
  • 13-4 Sensitivity Analysis
  • 13-5 Properties of Linear Models
  • 13-6 Infeasibility and Unboundedness
  • 13-7 A Larger Product Mix Model
  • 13-8 A Multiperiod Production Model
  • 13-9 A Comparison of Algebraic and Spreadsheet Models
  • 13-10 A Decision Support System
  • 13-11 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 13.1 Shelby Shelving
  • Chapter 14: Optimization Models
  • 14-1 Introduction
  • 14-2 Employee Scheduling Models
  • 14-3 Blending Models
  • 14-4 Logistics Models
  • 14-5 Aggregate Planning Models
  • 14-6 Financial Models
  • 14-7 Integer Optimization Models
  • 14-8 Nonlinear Optimization Models
  • 14-9 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 14.1 Giant Motor Company
  • Case 14.2 GMS Stock Hedging
  • Chapter 15: Introduction to Simulation Modeling
  • 15-1 Introduction
  • 15-2 Probability Distributions for Input Variables
  • 15-3 Simulation and the Flaw of Averages
  • 15-4 Simulation with Built-in Excel Tools
  • 15-5 Simulation with @RISK
  • 15-6 The Effects of Input Distributions on Results
  • 15-7 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 15.1 Ski Jacket Production
  • Case 15.2 Ebony Bath Soap
  • Appendix: Simulation with DADM_Tools
  • Chapter 16: Simulation Models
  • 16-1 Introduction
  • 16-2 Operations Models
  • 16-3 Financial Models
  • 16-4 Marketing Models
  • 16-5 Simulating Games of Chance
  • 16-6 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 16.1 College Fund Investment
  • Case 16.2 Bond Investment Strategy
  • Part 6: Advanced Data Analysis
  • Chapter 17: Data Mining
  • 17-1 Introduction
  • 17-2 Classification Methods.
  • 17-3 Clustering Methods
  • 17-4 Conclusion
  • Summary of Key Terms
  • Problems
  • Case 17.1 Houston Area Survey
  • References
  • Index.

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