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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
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100 1 |a Albright, S. Christian. 
245 1 0 |a Business Analytics :  |b Data Analysis & Decision Making. 
250 |a 7th ed. 
264 1 |a Mason, OH :  |b Cengage,  |c 2020. 
300 |a 1 online resource (914 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
505 0 |a 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. 
505 8 |a 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. 
505 8 |a 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. 
505 8 |a 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. 
505 8 |a 17-3 Clustering Methods -- 17-4 Conclusion -- Summary of Key Terms -- Problems -- Case 17.1 Houston Area Survey -- References -- Index. 
526 0 |a AA701- Master in Business Administration (MBA)  |z Syllabus Programme 
588 |a Description based on publisher supplied metadata and other sources. 
590 |a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.  
650 0 |a Microsoft Excel (Computer file). 
650 0 |a Decision making-Computer programs.. 
650 0 |a Industrial management-Statistical methods-Computer programs. 
655 4 |a Electronic books. 
700 1 |a Winston, Wayne L. 
776 0 8 |i Print version:  |a Albright, S. Christian  |t Business Analytics : Data Analysis & Decision Making  |d Mason, OH : Cengage,c2019  |z 9780357109953 
797 2 |a ProQuest (Firm) 
856 4 0 |u https://ezaccess.library.uitm.edu.my/login?url=https://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=6351080  |z View fulltext via EzAccess 
966 0 |a 2021  |b ProQuest Ebook Central  |c UiTM Library  |d Atirah Ruslan  |e Arshad Ayub Graduate Business School (AAGBS)  |f ProQuest 

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