Books › Applied regression analysis and other multivariable methods
Applied regression analysis and other multivariable methods
First published 1978 · 1051 pages
A rigorous but grounded journey through the logic of data, transforming abstract numbers into actionable insights.
What it feels like
Reading this book feels like sitting in a well-lit university library with a patient, highly knowledgeable professor guiding you through the thicket of statistical theory. The pace is necessarily steady, demanding focused attention as it builds from foundational concepts to complex multivariable models. Rather than drowning the reader in abstract mathematical proofs, the text maintains a pragmatic, problem-solving atmosphere, anchoring every equation in real-world applications and computer-based exercises. The mood is one of quiet, methodical rigor—a space where confusion slowly gives way to the deep satisfaction of intellectual clarity. It is a deeply rewarding experience for researchers and students who want to not just run statistical software, but truly understand the intuitive logic beneath the algorithms.
- Mood
- focused
- academic
- methodical
- intellectually rigorous
- Tone
- authoritative
- instructive
- pragmatic
- analytical
- encouraging
- Pace
- steady
- Themes
- problem solving · logical deduction · real-world application · data interpretation · methodological rigor
- The writing
- The writing is clear, structured, and highly technical, prioritizing intuitive explanations over dense mathematical proofs.
- The arc
- The reader moves from the daunting complexity of raw data to the satisfying clarity of structured, interpretable models.
- Who it's for
- Students, researchers, and data professionals seeking a practical, hands-on foundation in multivariable statistical techniques.
About the book
This bestseller helps to learn regression-analysis methods that one can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that one can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques.
Description from Open Library.
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