Download Model Based Inference in the Life Sciences: A Primer on Evidence PDF

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This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.

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• Paperback: 184 pages
• Publisher: Springer; 1st ed. 2008 edition (June 25, 2010)
• Language: English
• ISBN-10: 0387740732
• ISBN-13: 978-0387740737
• Product Dimensions: 0.4 x 5.9 x 8.9 inches
• Shipping Weight: 9.6 ounces (View shipping rates and policies)

Download Model Based Inference in the Life Sciences: A Primer on Evidence PDF

I am a graduate student in the life sciences and am new to information theory and multiple hypotheses and this book was really clear, "easy" to read and just plain made a lot of sense. The author is not afraid to share his opinion but what is nice is that you are clear on what is opinion and what is history or theory. I highly suggest this book for any first year graduate student since most departments are still not teaching this in the classroom.

By M. R. Jamieson

I use this book as a supplementary text for a graduate course. It's clearly written, and explains all of the multiple model AIC-based approach in simple terms that students that aren't especially quantitatively oriented can understand and apply the techniques.

By Milo Adkison