本书是数据统计分析领域的经典著作，堪称经典中的经典。本书有助于读者了解数据分析与回归的有关知识，并学习如何应用数据分析。在本书中，作者建议采用“凸规则”发现获得线性性状的转换方法。建议搭配《Tukey统计学讲义：探索性数据分析》一起购买。

1 Approaching Data Analysis
Introduction
1A The staircase and the shortcut to inference
1B Student's true contribution
1C Distributions and their troubles
1D A classical example: Wilson and Hilferty's analysis of Peirce's data
1E Kinds of nonnormality and robustness
1F The role of vague concepts
1G Other vague concepts
1H Indication, determination, or inference
Summary: Data analysis
2 Indication and Indicators
2A The value of indication
2B Examples of stopping with indication
2C Concealed inference
2D Choice of indicators
2E An example of choice of indicator
2F Indications of quality: Cross-validation
Summary: Indication and indicators
3 Displays and Summaries for Batches
3A Stem-and-leaf.
3B Medians, hinges, etc.
3C Mids and spreads
3D Subsampling
3E Exploratory plotting
3F Trends and running medians
3G Smoothing nonlinear regressions
3H Looking for patterns
3I Residuals more generally
3J Plotting and smoothing
Summary: Batch summaries and displays
4 Stralghtening Curves and Plots
The iden of straightening out curves
4A The ladder of re-expressions
4B Re-expressing y=x2
4C The bulging rule
4D More complicated curves
4E Scatter plots
Summary: Straightening curves
5 The Practice of Re-Expression
5A Kinds of numbers
5B Quick logs
5C Quick (square) roots and reciprocals
5D Quick re-expressions of counted fractions, percentages, etc.
5E Matching for powers and logs
5F Re-expressions for grades
5G Re-expressing ranks
5H First aid in re-expression
5I What to do with zeros—and infinities
Summary: Re-expression
6 Need We Re-Express?
General hints when re-expressed carrier is logx
7 Hunting out the Real Uncertainty
7A How ?/Vn can mislead
7B A further example of the need for direct assessment of variability
7C Choosing an error term
7D More detailed choices of error terms
7E Making direct assessment possible
7F Difficulties with direct assessment
7G Supplementary uncertainty and its combination with internal uncertainty
Summary: Hunting out the real uncertainty
8 A Method of Direct Assessment
8A The jackknife
Appendix to 8A
8B Examples with individuals
8C Jackknife using groups: Ratio estimation for a sample survey
8D A more complex example
8E Cross-validation in the example
8F Two simultaneous uses of "leave out one"
8G Dispersion of the p's
8H Further discussion of the example
Summary: The jackknife
9 Two- and More-Way Tables
9A PLUS analyses
9B Looking at two-way PL.US analyses
9C Taking advantage of levels
9D Polishing additive fits
9E Fitting one more constant
9F Using re-expression
9G Three- and more-way analyses
Summary:Two-way tables of responses
10 Robust and Resistant Measures
10A Resistance
10B Robustness
10C Robust and resistant estimates of location
10D Robust estimates of scale
10E Robust and resistant intervals
10F Resistant and robust regression
10G Multiple-component data
10H Closing comment
Summary: Resistant and robust techniques
11 Standardizing for Comparison
11A The simplest case
11B Direct standardization
11C Precision of directly standardized values
11D Difficulties with direct standardization
11E Indirect standardizing
11F Adjustment for broad categories
11G More than two broad categories
Summary: Standardizing for comparison
12 Regression for Fitting
Introduction
12A The two meanings of regression
12B Purposes of regression
12C Graphical fitting by stages
12D Collinearity
12E Linear dependence, exact and approximate
12F Keeping out what is imprecisely measured–Regression as exclusion
*12G Which straight line? (Optional)12H Using subsamples
Summary:Regression
13 Woes of Regression Coefficients
13A Meaning of