Statistics and Experimental Design for Toxicologists and Pharmacologists
Taylor & Francis

Statistics and Experimental Design for Toxicologists and Pharmacologists

Edition: 4th Edition
Subjects: Maths & Science, Probability & statistics
ISBN13: 9780367392482
Published: 07 Oct 2019

Format - Paperback / softback
By Shayne C. Gad

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A$104.80
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Statistics and Experimental Design for Toxicologists and Pharmacologists

A$104.80
A$104.80 A$131.00
Product description

Purposefully designed as a resource for practicing and student toxicologists, Statistics and Experimental Design for Toxicologists and Pharmacologists, Fourth Edition equips you for the regular statistical analysis of experimental data. Starting with the assumption of basic mathematical skills and knowledge, the author supplies a complete and systematic yet practical introduction to the statistical methodologists available for, and used in, the discipline. For every technique presented, a worked example from toxicology is also presented.

See what's new in the Fourth Edition:

  • The first practical guide to performing meta analysis allowing for using the power inherent in multiple similar studies
  • Coverage of Bayesian analysis and data analysis in pharmacology and toxicology
  • Almost 200 problems with solutions
  • Discussion of analysis of receptor binding assays, safety pharmacology assays and other standard types conducted in pharmacology
  • A new chapter explaining the basics of Good Laboratory Practices (GLPs)
  • For those with computer skills, this edition has been enhanced with the addition of basic SAS

    Written specifically for toxicologists and pharmacologists, the author draws on more than 30 years of experience to provide understanding of the philosophical underpinnings for the overall structure of analysis. The book's organization fosters the ordered development of skills and yet still facilitates ease of access to information as needed. This Fourth Edition gives you the tools necessary to perform rigorous and critical analysis of experimental data and the insight to know when to use them.
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