Business Analytics with R
1
Introduction
1.1
Overview
1.2
Acknowledgements
2
Data Science
2.1
Overview
2.2
Get
2.3
Clean
2.4
Organize
2.5
Model
2.6
Visualize
2.7
Review
3
Operations
3.1
Transportation Problems
3.2
Economic Order Quantity
3.3
Economic Production Quantity
3.4
News Vendor Model
3.5
Production Scheduling
3.6
Review
4
Research and Development
4.1
Sentiment Analysis
4.2
Six Sigma
4.3
The Product Life Cycle Model
4.4
Predicting Black Swans
4.5
Review
5
Purchasing
5.1
Supplier Risk
5.2
Time to Recovery
5.3
Time to Survive
5.4
Commodity Price Sensitivity
5.5
Reorder Point
5.6
Review
6
Marketing
6.1
Optimal Product Mix
6.2
Pricing with Subjective Demand
6.3
Determining Customer Value
6.4
Category Management
6.5
Review
7
Human Resources
7.1
Measuring Engagement
7.2
Employee Turnover
7.3
Employee Performance
7.4
Recruitment and Selection
7.5
Review
8
Finance
8.1
Financial Calculations
8.1.1
Amortization Period
8.1.2
Amortization Table
8.1.3
IRR Internal Rate of Return
8.1.4
NPV Net Present Value
8.1.5
TVM Time Value of Money
8.2
Time Series Basics
8.3
Multivariate Adaptive Regression
8.4
Forecasting with Optimization
8.5
Review
9
Deployment
9.1
Markdown
9.2
Automate PowerPoint
9.3
Create a Desktop Application
9.4
Review
10
Final Words
11
Appendix
11.1
About R
11.2
Software Requirements
11.3
Basics
11.3.1
Operators
11.3.2
Functions
11.3.3
Data Types
11.3.4
Loops
11.4
References
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Business Analytics with R - DRAFT
Business Analytics with R - DRAFT
By Jeffrey Monroe
