Business Analytics with R
1
Introduction
1.1
Overview
1.2
Preliminaries
1.3
Software Requirements
1.4
Acknowledgements
2
Basics
2.1
Operators
2.2
Functions
2.3
Data Types
2.4
Loops
2.5
Review
3
Data Science
3.1
Overview
3.2
Get
3.3
Clean
3.4
Organize
3.5
Model
3.6
Visualize
3.7
Review
4
Operations
4.1
Transportation Problems
4.2
Economic Order Quantity
4.3
Economic Production Quantity
4.4
News Vendor Model
4.5
Production Scheduling
4.6
Review
5
Research and Development
5.1
Sentiment Analysis
5.2
Six Sigma
5.3
The Product Life Cycle Model
5.4
Predicting Black Swans
5.5
Review
6
Purchasing
6.1
Supplier Risk
6.2
Time to Recovery
6.3
Time to Survive
6.4
Commodity Price Sensitivity
6.5
Reorder Point
6.6
Review
7
Marketing
7.1
Optimal Product Mix
7.2
Pricing with Subjective Demand
7.3
Determining Customer Value
7.4
Category Management
7.5
Review
8
Human Resources
8.1
Measuring Engagement
8.2
Employee Turnover
8.3
Employee Performance
8.4
Recruitment and Selection
8.5
Review
9
Finance
9.1
Financial Calculations
9.1.1
Amortization Period
9.1.2
Amortization Table
9.1.3
IRR Internal Rate of Return
9.1.4
NPV Net Present Value
9.1.5
TVM Time Value of Money
9.2
Time Series Basics
9.3
Multivariate Adaptive Regression
9.4
Forecasting with Optimization
9.5
Review
10
Deployment
10.1
Markdown
10.2
Automate PowerPoint
10.3
Create a Desktop Application
10.4
Review
11
Final Words
12
Appendix
12.1
References
Published with bookdown
Business Analytics with R - DRAFT
Business Analytics with R - DRAFT
By Jeffrey Monroe
