## 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.

## 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.

## Statistics Explained

Author: Perry R. Hinton
Publisher: Routledge
ISBN: 9781317753926
Release Date: 2014-03-21
Genre: Psychology

Statistics Explained is an accessible introduction to statistical concepts and ideas. It makes few assumptions about the reader’s statistical knowledge, carefully explaining each step of the analysis and the logic behind it. The book: provides a clear explanation of statistical analysis and the key statistical tests employed in analysing research data gives accessible explanations of how and why statistical tests are used includes a wide range of practical, easy-to-understand worked examples. Building on the international success of earlier editions, this fully updated revision includes developments in statistical analysis, with new sections explaining concepts such as bootstrapping and structural equation modelling. A new chapter - ‘Samples and Statistical Inference’ - explains how data can be analysed in detail to examine its suitability for certain statistical tests. The friendly and straightforward style of the text makes it accessible to all those new to statistics, as well as more experienced students requiring a concise guide. It is suitable for students and new researchers in disciplines including Psychology, Education, Sociology, Sports Science, Nursing, Communication, and Media and Business Studies. Presented in full colour and with an updated, reader-friendly layout, this new edition also comes with a companion website featuring supplementary resources for students. Unobtrusive cross-referencing makes it the ideal companion to Perry R. Hinton’s SPSS Explained, also published by Routledge. Perry R. Hinton has many years of experience in teaching statistics to students from a wide range of disciplines and his understanding of the problems students face forms the basis of this book.

## 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!

## 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.

## Statistics at the Bench

Author: Martina Bremer
Publisher:
ISBN: STANFORD:36105215291449
Release Date: 2010
Genre: Mathematics

Statistics at the Bench is a convenient bench-side companion for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses. The expectations for biologists to have a more complete understanding of statistics are growing rapidly. New technologies and new areas of science, such as microarrays, next-generation sequencing, and proteomics, have dramatically increased the need for quantitative reasoning among biologists when designing experiments and interpreting results. Even the most routine informatics tools rely on statistical assumptions and methods that need to be appreciated if the scientific results are to be correct, understood, and exploited fully. This book is not a textbook. It is an essential handbook for working scientists. Statistics at the Bench provides a simple refresher for those who have forgotten what they once knew, and an overview for those wishing to use more quantitative reasoning in their research. Statistical methods, as well as guidelines for the interpretation of results, are explained using simple examples. Throughout the book, examples are accompanied by detailed Excel commands for easy reference.

## Data Analysis for Chemistry

Author: Professor of Analytical Chemistry D Brynn Hibbert
Publisher: OUP USA
ISBN: 0195162102
Release Date: 2006
Genre: Science

Covers topics including measurements, means and confidence intervals, hypothesis testing, analysis of variance, and calibration models. The end result is a compromise between recipes of how to perform different aspects of data analysis and basic information on the background principles behind the recipes to be performed.

## 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 the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, 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 in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

## 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.

## R in a Nutshell

Publisher: "O'Reilly Media, Inc."
ISBN: 9781449358228
Release Date: 2012-09-26
Genre: Computers

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports. Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop. Get started quickly with an R tutorial and hundreds of examples Explore R syntax, objects, and other language details Find thousands of user-contributed R packages online, including Bioconductor Learn how to use R to prepare data for analysis Visualize your data with R’s graphics, lattice, and ggplot2 packages Use R to calculate statistical fests, fit models, and compute probability distributions Speed up intensive computations by writing parallel R programs for Hadoop Get a complete desktop reference to R

## Basic Statistics

Author: Olive Jean Dunn
Publisher: John Wiley & Sons
ISBN: 0470496851
Release Date: 2009-08-11
Genre: Mathematics