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The Practice of Statistics in the Life Sciences

The Practice of Statistics in the Life Sciences
Author: Brigitte Baldi
Publisher: Macmillan Higher Education
Total Pages: 756
Release: 2013-12-15
Genre: Mathematics
ISBN: 1464133212

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This remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore’s The Basic Practice of Statistics, PSLS mirrors that #1 bestseller’s signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.


Practice of Statistics in the Life Sciences

Practice of Statistics in the Life Sciences
Author: Brigitte Baldi
Publisher: WH Freeman
Total Pages: 340
Release: 2018-03-08
Genre: Mathematics
ISBN: 9781319187606

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This remarkably engaging textbook is the perfect learning resource for undergraduate and postgraduate biology students studying statistics and data analysis. Part of the best-selling Moore family of statistics books, it covers essential statistical topics with examples and exercises drawn from across the field of life sciences, including disciplines such as nursing, public health, and allied health. Based on David Moore’s classic The Basic Practice of Statistics, this textbook applies the bestseller’s signature emphasis on statistical thinking to the world of life sciences, helping engage students and underlining how statistics can directly apply to the projects they’re working on. This textbook will be available on SaplingPlus, a highly-intelligent online teaching and learning tool which will be available for statistics in Autumn 2018.


Loose-Leaf Version for Practice of Statistics in the Life Sciences, Digital Update

Loose-Leaf Version for Practice of Statistics in the Life Sciences, Digital Update
Author: Brigitte Baldi
Publisher: Macmillan Higher Education
Total Pages: 3008
Release: 2022-05-09
Genre: Mathematics
ISBN: 1319416853

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The Practice of Statistics in the Life Sciences helps students understand how to apply essential statistical skills across life sciences including nursing, public health, and allied health.


Practice of Statistics in the Life Sciences - Pack

Practice of Statistics in the Life Sciences - Pack
Author: Brigitte Baldi
Publisher: WH Freeman
Total Pages:
Release:
Genre: Medical
ISBN: 9781949374025

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This is the pack for Practice of Statistics in the Life Sciences, including the textbook and the SaplingPlus 12 month access card.


Student Solution Manual for The Practice of Statistics in the Life Sciences

Student Solution Manual for The Practice of Statistics in the Life Sciences
Author: Brigitte Baldi
Publisher: Macmillan
Total Pages: 259
Release: 2011-02-04
Genre: Mathematics
ISBN: 1429266856

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This is an introduction to the uses and applications of statistics in the life sciences with a data analysis approach. The book provides step-by-step solutions along with summaries of the key concepts needed to solve the problems.


Modern Statistics for the Life Sciences

Modern Statistics for the Life Sciences
Author: Alan Grafen
Publisher: Oxford University Press
Total Pages: 368
Release: 2002-03-21
Genre: Mathematics
ISBN: 0199252319

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Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. The book aims to put this methodology firmly within the grasp of undergraduates.


Data Analysis for the Life Sciences with R

Data Analysis for the Life Sciences with R
Author: Rafael A. Irizarry
Publisher: CRC Press
Total Pages: 537
Release: 2016-10-04
Genre: Mathematics
ISBN: 1498775861

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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.