Statistics Explained

Author: Steve McKillup
Publisher: Cambridge University Press
ISBN: 9781139502948
Release Date: 2011-11-03
Genre: Medical

An understanding of statistics and experimental design is essential for life science studies, but many students lack a mathematical background and some even dread taking an introductory statistics course. Using a refreshingly clear and encouraging reader-friendly approach, this book helps students understand how to choose, carry out, interpret and report the results of complex statistical analyses, critically evaluate the design of experiments and proceed to more advanced material. Taking a straightforward conceptual approach, it is specifically designed to foster understanding, demystify difficult concepts and encourage the unsure. Even complex topics are explained clearly, using a pictorial approach with a minimum of formulae and terminology. Examples of tests included throughout are kept simple by using small data sets. In addition, end-of-chapter exercises, new to this edition, allow self-testing. Handy diagnostic tables help students choose the right test for their work and remain a useful refresher tool for postgraduates.

Statistics Explained

Author: Steve McKillup
Publisher: Cambridge University Press
ISBN: 1139445812
Release Date: 2005-12-15
Genre: Medical

Statistics Explained is a reader-friendly introduction to experimental design and statistics for undergraduate students in the life sciences, particularly those who do not have a strong mathematical background. Hypothesis testing and experimental design are discussed first. Statistical tests are then explained using pictorial examples and a minimum of formulae. This class-tested approach, along with a well-structured set of diagnostic tables will give students the confidence to choose an appropriate test with which to analyse their own data sets. Presented in a lively and straight-forward manner, Statistics Explained will give readers the depth and background necessary to proceed to more advanced texts and applications. It will therefore be essential reading for all bioscience undergraduates, and will serve as a useful refresher course for more advanced students.

Geostatistics Explained

Author: Steve McKillup
Publisher: Cambridge University Press
ISBN: 9780521763226
Release Date: 2010-03-25
Genre: Mathematics

This reader-friendly introduction to geostatistics demystifies complex concepts and makes formulas and statistical tests easy to apply. With wide-ranging examples from topics across the Earth and environmental sciences, and worked examples at the end of each chapter, this book can be used for undergraduate courses or for self-study and reference.

Understanding Regression Analysis

Author: Larry D. Schroeder
Publisher: SAGE
ISBN: 0803927584
Release Date: 1986-04-01
Genre: Medical

The authors have provided beginners with a background to the frequently-used technique of linear regression. It is not intended to be a substitute for a course or textbook in statistics, but rather a stop-gap for students who encounter empirical work before undertaking a statistics course. It provides a heuristic explanation of the procedures and terms used in regression analysis and has been written at the most elementary level.

A Primer in Biological Data Analysis and Visualization Using R

Author: Gregg Hartvigsen
Publisher: Columbia University Press
ISBN: 9780231537049
Release Date: 2014-02-18
Genre: Science

R is a popular programming language that statisticians use to perform a variety of statistical computing tasks. Rooted in Gregg Hartvigsen's extensive experience teaching biology, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio to the organization, computation, and visualization of biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to express data in histograms, boxplots, barplots, scatterplots, before/after line plots, pie charts, and graphs. He covers data normality, outliers, and nonnormal data and examines frequently used statistical tests with one value and one sample; paired samples; more than two samples across a single factor; correlation; and linear regression. The volume also includes a section on advanced procedures and a final chapter on possible extensions into programming, featuring a discussion of algorithms, the art of looping, and combining programming and output.

Data Analysis for the Life Sciences with R

Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 9781498775861
Release Date: 2016-10-04
Genre: Mathematics

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.

Cartoon Guide to Statistics

Author: Larry Gonick
Publisher: Harper Collins
ISBN: 9780062731029
Release Date: 1993-07-14
Genre: Study Aids

If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trails on "People's Court," or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy. The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more—all explained in simple, clear, and yes, funny illustrations. Never again will you order the Poisson Distribution in a French restaurant!

Sexual Selections

Author: Marlene Zuk
Publisher: Univ of California Press
ISBN: 0520240758
Release Date: 2003
Genre: Science

A provocative tour of recent findings in animal sexuality and evolutionary biology seeks to demonstrate how anthropomorphism and gender politics have affected our knowledge of the natural world and shows how a broader approach, based on feminist biology, can bring about a more rounded understanding.

Statistics Translated

Author: Steven R. Terrell
Publisher: Guilford Press
ISBN: 9781462503216
Release Date: 2012-04-02
Genre: Social Science

Written in a humorous and encouraging style, this text shows how the most common statistical tools can be used to answer interesting real-world questions, presented as mysteries to be solved. Engaging research examples lead the reader through a series of six steps, from identifying a researchable problem to stating a hypothesis, identifying independent and dependent variables, and selecting and interpreting appropriate statistical tests. All techniques are demonstrated both manually and with the help of SPSS software. The book provides students and others who may need to read and interpret statistically based research with the essential knowledge and skills needed to make decisions based on data. ? Pedagogical Features Include: *Checklists of key words and formulas in every chapter. *Examples of SPSS screenshots used for analyzing data. *Cautionary notes plus "Putting It All Together" section recaps. *End-of-chapter self-quizzes (with full answers and explanations). *Glossary of terms.

Measuring Behaviour

Author: Paul Martin
Publisher: Cambridge University Press
ISBN: 0521446147
Release Date: 1993-04-22
Genre: Psychology

Measuring Behaviour is a guide to the principles and methods of quantitative studies of behavior, with an emphasis on techniques of direct observation, recording, and analysis. In the new edition, all sections have been updated and revised, particularly those dealing with the technology of recording behavior, and there are new sections on regression and multivariate statistics. As with the first edition, the authors strive for brevity and clarity of presentation.

Data Analysis for Chemistry

Author: D. Brynn Hibbert
Publisher: OUP USA
ISBN: 9780195162103
Release Date: 2006
Genre: Science

Annotation. Definitions, Questions, and Useful Functions: Where to Find Things and What To Do1. Introduction2. Describing Data3. Hypothesis Testing4. Analysis of Variance5. Calibration.

Head First Data Analysis

Author: Michael Milton
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596153939
Release Date: 2009-07-24
Genre: Business & Economics

A guide for data managers and analyzers shares guidelines for identifying patterns, predicting future outcomes, and presenting findings to others; drawing on current research in cognitive science and learning theory while covering such additional topics as assessing data quality, handling ambiguous information, and organizing data within market groups. Original.

An Introduction to Statistical Learning

Author: Gareth James
Publisher: Springer Science & Business Media
ISBN: 9781461471387
Release Date: 2013-06-24
Genre: Mathematics

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.