PREFACE
1 INTRODUCTION
Data Analysis
What's in This Book
What's with the Workshops?
What's with the Math?
What You'll Need
What's Missing

PART I Graphics: Looking at Data
2 A SINGLE VARIABLE: SHAPE AND DISTRIBUTION
Dot andJitter Plots
Histograms and Kernel Density Estimates
The Cumu/atiue Distribution Function
Rank-Order Plots and Lilt Charts
Only When Appropriate: Summary Statistics and Box Plots
Workshop: NumPy
Further Reading
3 TWO VARIABLES: ESTABLISHING RELATIONSHIPS
Scatter Plots
Conquering Noise: 5moothing
Logarithmic Plots
Banking
Linear ReRression and All That
Shouwing What's Important
Graphical Analysis and Presentation Graphics
Workshop: matplotlib
Further Reading
TIME AS A VARIABLE: TIME-SERIES ANALYSIS
Examples
The Task
Smoothing
Don't Ouerlook the Obuious!
The Correlation Function
Optional: Filters and Conuolutions
Workshop: scipy.signal
Further ReadinR
5 MORE THAN TWO VARIABLES: GRAPHICAL MULTIVARIATE ANALYSIS
False-Color Plots
A Lot at a Glance: Multiplots
Composition Problems
Nouel Plot Types
Interactiue Explorations
Workshop: Tools for Multiuariate Graphics
Further ReadinR
6 INTERMEZZO: A DATA ANALYSIS SESSION
A Data Analysis Session
Workshop: gnuplot
Further ReadinR

PART II Analyticg: Modeling Data
7 GUESSTIMATION AND THE BACK OF THE ENVELOPE
Principles of Guesstimation
How Good Are Those Numbers?
Optional: A Closer Look at Perturbation Theory and
Error PropaRation
Workshop: The Gnu Scientific Library (GSL)
Further Reading
8 MODELS FROM SCALING ARGUMENTS
Models
ArRuments from Scale
Mean-Field Approximations
Common Time-Euolution Scenarios
Case Study: How Many Seruers Are Best?
Why Modeling?
Workshop: Sage
Further Reading
9 ARGUMENTS FROM PROBABILITY MODELS
The. Binomial Distribution and Bernoulli Trials
The Gaussian Distribution and the Central Limit Theorem
Power-Law Distributions and Non-Normal Statistics
Other Distributions
Optional: Case Study--Unique Visitors ouer Time
Workshop: Power-Law Distributions
Further Reading
10 WHAT YOU REALLY NEED TO KNOW ABOUT CLASSICAL STATISTICS
Genesis
Statistics Defined
Statistics Explained
Controlled Experiments Versus Obseruationa} Studies
Optional: Bayesian Statistics--The Other Point of View
Workshop: R
Further Reading
11 INTERMEZZO:MYTHBUSTING--BIGFOOT, LEAST SQUARES, AND ALL THAT
How to Auerage Auerages
The Standard Deuiation
Least Squares
Further Reading

PART III Computation: Mininhg Data
12 SIMULATIONS
A Warm-Up Question
Monte Carlo Simulations
Resampling Methods
Workshop: Discrete Euent Simulations with Simpy
Further Reading
13 FINDING CLUSTERS
What Constitutes a Cluster?
Distance and Similarity Measures
Clustering Methods
Pre-and Postprocessing
Other ThouRhts
A Special Case: Market BasketAnalysis
A Word of WarninR
Workshop: P/cluster and the C Clustering Library
Further Reading
14 SEEING THE FOREST FOR THE TREES: FINDING
IMPORTANT ATTRIBUTES
Principal Component Analysis
Visual Techniques
Kohonen Maps
Workshop: PCA with R
Further Readin2
15 INTERMEZZO:WHEN MORE IS DIFFERENT
A Horror Story
Some Suggestions
What About Map/Reduce?
Workshop: Generating Permutations
Further Reading

PART IV Applications: Using Data
16 REPORTING, BUSINESS INTELLIGENCE, AND DASHBOARDS
Business Intelligence
Corporate Metrics and Dashboards
Data Quality Issues
Workshop: Berkeley DB and SQLite
Further Reading
17 FINANCIAL CALCULATIONS AND MODELING
The Time Value o[ Money
Uncertainty in Planning and Opportunity Costs
Cost Concepts and Depreciation
Should You Care?
Is This All That Matters?
Workshop: The Newsuendor Problem
Further Reading
18 PREDICTIVE ANALYTICS
Introduction
Some Classification Terminology
Algorithms for Classification
The Process
The Secret Sauce
The Nature o[ Statistical Learning
Workshop: Two Do-lt-Yoursel Classifiers
Further Reading
19 EPILOGUE: FACTS ARE NOT REALITY
A PROGRAMMING ENVIRONMENTS FOR SCIENTIFIC COMPUTATION
AND DATA ANALYSIS
Software Tools
A Catalog of Scientific Software
Writing Your Own
Further Reading
B RESULTS FROM CALCULUS
Common Functions
Calculus
Useful Tricks
Notation and Basic Math
Where to Go from Here
Further Readin9
WORKING WITH DATA
Sources for Data
Cleanin9 and ConditioninR
Sarnplin9
Data File Formats
The Care and Feeding of Your Data Zoo
Skills
Terminology
Further Fleadin9
INDEX