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Business Analytics

Autor Arul Mishra, Himanshu Mishra
en Limba Engleză Paperback – 15 mar 2024
Businesses typically encounter problems first and then seek out analytical methods to help in decision making. Business Analytics: Solving Business Problems with R by Arul Mishra and Himanshu Mishra offers practical, data-driven solutions for today¿s dynamic business environment. This text helps students see the real-world potential of analytical methods to help meet their business challenges by demonstrating the application of crucial methods such as neural nets, natural language processing, and boosted decision trees. Applications of these methods to pricing models, social sentiment analysis, and branding with company experiences like Frito-Lay, Netflix, and Zappos show students how to use the results of research in real business settings. Step-by-step R code with commentary gives readers the tools to adapt each method to their business settings. The book offers comprehensive coverage across diverse business domains, including finance, marketing, human resources, operations, and accounting.
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Specificații

ISBN-13: 9781071815236
ISBN-10: 1071815237
Pagini: 344
Dimensiuni: 187 x 231 x 2 mm
Greutate: 0.68 kg
Ediția:1
Editura: SAGE Publications

Cuprins

Part 1. Business Environment Analytics
Chapter 1: The external environment of a business
Chapter 2: Monitoring the Macroeconomic Environment
Chapter 3: Monitoring the Competitive Environment using Principal Component Analysis
Chapter 4: Monitoring the Social Environment using Text Analysis
Part 2. Marketing Analytics
Chapter 5: Market Segmentation using Clustering Algorithms
Chapter 6: Predicting Price with Neural Nets
Chapter 7: Advertising and Branding with A/B Testing
Chapter 8: Customer Analytics using Neural Nets
Part 3. Financial and Accounting Analytics
Chapter 9: Loan Charge-off Prediction using an Explainable Model
Chapter 10: Analyzing Financial Performance with LASSO
Chapter 11: Forensic Accounting using Outlier Detection Algorithms
Part 4. Operations and Supply Chain Analytics
Chapter 12: Predicting Decision Uncertainty using Random Forests
Chapter 13: Predicting Employee Satisfaction using Boosted Decision Trees
Chapter 14: New Product Development with A/B Testing
Part 5. Business Ethics and Analytics
Chapter 15: Fairness in Business Analytics
Part 6. Technical Appendix