A Minimal Book Example
Preface
1
Introduction
1.1
Business Statistics
1.2
Defining Data Science
1.2.1
Venn Diagram of Data Science
1.3
Data Science is Science
1.4
Big Data
1.5
Data Science Case Studies
1.5.1
Signet Bank
1.5.2
Target
1.5.3
Walmart
1.5.4
Obama Campaign
1.5.5
Identifying Place
1.5.6
Pruning Trees in NYC
1.5.7
The Information Architecture of Medicine is Broken
1.5.8
Love in the Time of Data
1.5.9
Booz/Allen/Hamilton Data Science
1.6
Conclusion
1.7
Review
1.8
Exercises
2
Data Science Process
2.1
The Process
2.2
Side Note on Data
2.3
Stages of Data Science
2.4
Agile Data Science Pyramid
2.5
ASK
2.6
CoNVO
2.7
CoNVO Examples
2.7.1
Refugee Non-Profit
2.7.2
Marketing Department
2.7.3
Media Organization
2.7.4
Advocacy Group
2.8
Resistance
2.9
Conclusion
2.10
Review
2.11
Exercises
2.12
Additional Resources
3
Systems Theory
3.1
System Dynamics
3.2
What is a System?
3.3
Causal Loop Diagram
3.4
Heroin Model
3.5
Email Model
3.6
Conclusion
3.7
Review
3.8
Exercises
3.9
Additional Resources
4
Probability
4.1
From Systems Thinking to Probability
4.2
Definition of Probability
4.3
Axioms of Probability
4.3.1
Notation
4.4
Types of Probability
4.4.1
Joint Probability
4.4.2
Conditional Probability
4.4.3
Marginal or Prior Probability
4.5
Rules of Probability
4.5.1
Monotonicity
4.5.2
Negation
4.5.3
Total Probability
4.5.4
Chain Rule
4.5.5
Bayes Rule
4.6
Independence and Conditional Independence
4.7
Probabilistic Fallacies
4.7.1
Conjunction Fallacy
4.7.2
Gambler’s Fallacy and Hot-Streak Fallacy
4.7.3
Inverse Probability Fallacy
4.7.4
Base Rate Fallacy
4.7.5
Prosecutor’s Fallacy
4.8
Applications
4.8.1
Applications in General Probability
4.8.2
Applications of Bayes Rule
4.9
Probability and Simulation
4.9.1
Cities
4.9.2
What do we know?
4.10
Conclusion
5
Final Words
References
Published with bookdown
Fundamentals of Data Science (R Edition)
Chapter 5
Final Words
We have finished a nice book.