Handbook of Functional MRI Data Analysis

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Handbook of Functional MRI Data Analysis Info

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Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook for Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM, and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling, and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software..


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Persuader (Jack Reacher)

An elite ex-military cop who left the service years ago, he’s moved from place to place…without family…without possessions…without commitments.

And without fear. Which is good, because trouble—big, violent, complicated trouble—finds Reacher wherever he goes. And when trouble finds him, Reacher does not quit, not once…not ever.

But some unfinished business has now found Reacher. And Reacher is a man who hates unfinished business.

Ten years ago, a key investigation went sour and someone got away with murder. Now a chance encounter brings it all back. Now Reacher sees his one last shot. Some would call it vengeance. Some would call it redemption. Reacher would call it…justice.

An Introduction to Experimental Design and Statistics for Biology

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An Introduction to Experimental Design and Statistics for Biology Description

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This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.

This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.

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Logistic Regression: A Self-Learning Text (Statistics for Biology and Health)

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Logistic Regression: A Self-Learning Text (Statistics for Biology and Health) Info

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This is the second edition of this text on logistic regression methods. As in the first edition, each chapter contains a presentation of its topic in "lecture-book" format together with objectives, an outline, key formulae, practice exercises, and a test. The "lecture- book" has a sequence of illustrations and formulae in the left column of each page and a script (i.e., text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented.

This second edition includes five new chapters and an appendix. The new chapters are: Chapter 9. Polytomous Logistic Regression; Chapter 10. Ordinal Logistic Regression; Chapter 11. Logistic Regression for Correlated Data: GEE; Chapter 12. GEE Examples; Chapter 13. Other Approaches for Analysis of Correlated Data.

Chapters 9 and 10 extend logistic regression to response variables that have more than two categories. Chapters 11-13 extend logistic regression to generalized estimating equations (GEE) and other methods for analyzing correlated response data. The appendix "Computer Programs for Logistic Regression" provides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The software packages considered are SAS® Version 8.0, SPSS® Version 10.0 and STATA Version 7.0.

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