Business Analytics (eBook)

Solving Business Problems With R

Arul Mishra, Himanshu Mishra (Autoren)

eBook Download: EPUB

2024
529 Seiten
Sage Publications, Inc (Verlag)
978-1-0718-1528-1 (ISBN)

Inhalt

Part 1. Business Environment Analytics
Chapter 1: The external environment of a business
What Is a Business?
Internal and External Environment of a Business
Using Analytics to Understand the Business Environment
Chapter 2: Monitoring the Macroeconomic Environment
Defining the Macroeconomic Environment
Impact of Macroeconomic Factors on Business Outcomes
Regression for Prediction
Application of Linear Regression for Prediction
A Few Things to Remember
Implementation Using R: Predicting Units Ordered for MedDiagnostics
Understanding the Chapter
Chapter 3: Monitoring the Competitive Environment using Principal Component Analysis
The Competitive Environment of a Business
Visualization Using Principal Component Analysis
Application of PCA for Competitor Analysis
Other Uses of PCA
Implementation Using R: Competitor Analysis
Appendix: Technical Details of PCA
Understanding the Chapter
Chapter 4: Monitoring the Social Environment using Text Analysis
Understanding the Social Environment
Defining Text Data
Converting Qualitative Text Data to a Quantifiable Form
Analyzing Text Data
Choice of Meat Versus Meatless Options: A Reflection of the Social Environment
Other Text Analysis Methods
Implementation Using R: Choice of Meat Versus Meatless Options
Understanding the Chapter
Part 2. Marketing Analytics
Chapter 5: Market Segmentation using Clustering Algorithms
Segmenting Customers
Targeting Potential Customers
Positioning the Product in Customers’ Minds
Data-Driven Segmentation
Clustering Algorithms for Segmentation
Implementation Using R: Segmentation Using k-means and k-medoid
Understanding the Chapter
Chapter 6: Predicting Price with Neural Nets
Understanding Product Pricing
The Power of Pricing
Role of Analytics in Price Prediction
The Architecture of Neural Networks
A Deep Dive Into Neural Nets
Predicting House Prices Using Neural Nets
Implementation Using R: Predicting House Prices
Understanding the Chapter
Chapter 7: Advertising and Branding with A/B Testing
Advertising: Spreading the Message
Causal vs. Correlational
A/B Testing for Advertising Effectiveness
Steps in A/B Testing
Experimental Design to Test for Effective Advertisement
Machine-Learning-Based A/B Testing for Finding Effective Advertisements
Implementation Using R: A/B Testing for Advertising Effectiveness
Understanding the Chapter
Chapter 8: Customer Analytics using Neural Nets
Retaining Existing Customers
Rationale for a Defensive Strategy
Monitoring Satisfaction
Past Behavior as a Predictor of Churn
Predicting Customer Drop-Off Using Neural Nets
Implementation Using R: Predicting Customer Churn
Understanding the Chapter
Part 3. Financial and Accounting Analytics
Chapter 9: Loan Charge-off Prediction using an Explainable Model
Using Analytics for Financial Decisions
Risk Assessment: External Versus Internal Factors
Credit Underwriting: Protecting Against Risk
Logistic Regression
Using Logistic Regression for Charge-Off Prediction
Implementation Using R: Loan Approval
Understanding the Chapter
Chapter 10: Analyzing Financial Performance with LASSO
Financial Health of a Business
Importance of Forecasting Financial Health of the Business
Importance of Knowing Financial Health for Lenders
Importance of Knowing a Business’s Financial Health for Investors
Forecasting Financial Health
Multicollinearity
Using Penalized Regression for Evaluating Financial Health
Implementation Using R: Evaluating the Health of a Business
Appendix: Glossary of Financial Terms
Understanding the Chapter
Chapter 11: Forensic Accounting using Outlier Detection Algorithms
Machine Learning for Accounting
Forensic Accounting
Machine Learning for Forensic Accounting
Understanding Outliers
Detecting Fraudulent Transactions Using Loop
Business Insights and Conclusion
Implementation Using R: Outlier Detection for Identifying Fraudulent Transactions
Appendix: Glossary of Accounting Terms
Understanding the Chapter
Part 4. Operations and Supply Chain Analytics
Chapter 12: Predicting Decision Uncertainty using Random Forests
Decision-Making Under Uncertainty
Features of Decision Uncertainty
Backorder and Its Implications
Machine-Learning Options to Aid in Decision-Making Under Uncertainty
Random Forest
Backorder Prediction Using Random Forests
Business Insights and Summary
Implementation Using R: Backorder Prediction
Understanding the Chapter
Chapter 13: Predicting Employee Satisfaction using Boosted Decision Trees
Employee Satisfaction Drives Customer Satisfaction
Measuring Employee Satisfaction
Gradient-Boosted Trees
Using Boosted Decision Trees to Understand What Impacts Job Satisfaction
Business Insights and Summary
Implementation Using R: Employee Satisfaction
Understanding the Chapter
Chapter 14: New Product Development with A/B Testing
Innovations in the Marketplace
New Product Development Stages
The Importance of Testing and Market Research
The Intricacies of A/B Testing
Using A/B Testing to Test Gaming Prototypes
Using the A/B Test in New Product Development
Implementation Using R: The A/B Test
Understanding the Chapter
Part 5. Business Ethics and Analytics
Chapter 15: Fairness in Business Analytics
Introduction
What Are the Causes Behind Algorithmic Unfairness?
Mitigating Unfairness
Implementation Using Python: Debiasing an Algorithm
Understanding the Chapter
Part 6. Technical Appendix

Produkt-Details

• Erscheint lt. Verlag: 5.3.2024
• Verlagsort: Thousand Oaks
• Sprache: englisch
• Themenwelt: Sachbuch/Ratgeber ► Freizeit / Hobby ► Sammeln / Sammlerkataloge
• Schlagworte: Analytical Methods • Arul Mishra • Business Analysis • Business Analytics • Business Analytics with R • Business Decisions • Himanshu Mishra • machine learning • RStudio • statistical modeling
• ISBN-10: 1-0718-1528-8 / 1071815288
• ISBN-13: 978-1-0718-1528-1 / 9781071815281