Data Analysis and Regression A Second Course

Two mainstreams intermingle in this treatment of practical statistics: (a) a sequence of philosophical attitudes the student needs for effective data analysis, and (b) a flow of useful and adaptable techniques that make it possible to put these attitudes to work.

Approaching Data Analysis
Indication and Indicators
Displays and Summaries for Batches
Straightening Curves and Plots
The Practice of Re-expression
Need We Reexpress?
Hunting Out the Real Uncertainty
A Method of Direct Assessment
Two-and More-way Tables
Robust and Resistant Measures of Location and Scale
Standardizing for Comparison
Regression for Fitting
Woes of Regression Coefficients
Mechanisms Usually Operating in Linear Fitting
Guided Regression
Examining Regression Residuals
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Data Analysis and Regression A Second Course in Statistics

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