Beginner's guide to spatial, temporal,and spatial-temporal ecological data analysis with R-INLA

Beginner's guide to spatial, temporal,and spatial-temporal ecological data analysis with R-INLA PDF Author: Alain F. Zuur
Publisher:
ISBN: 9780957174191
Category : Ecology
Languages : en
Pages : 362

Get Book Here

Book Description

Beginner's guide to spatial, temporal,and spatial-temporal ecological data analysis with R-INLA

Beginner's guide to spatial, temporal,and spatial-temporal ecological data analysis with R-INLA PDF Author: Alain F. Zuur
Publisher:
ISBN: 9780957174191
Category : Ecology
Languages : en
Pages : 362

Get Book Here

Book Description


Statistics II for Dummies

Statistics II for Dummies PDF Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
ISBN: 0470466464
Category : Mathematics
Languages : en
Pages : 411

Get Book Here

Book Description
The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.

Spatial and Spatio-temporal Bayesian Models with R - INLA

Spatial and Spatio-temporal Bayesian Models with R - INLA PDF Author: Marta Blangiardo
Publisher: John Wiley & Sons
ISBN: 1118326555
Category : Mathematics
Languages : en
Pages : 322

Get Book Here

Book Description
Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations

Bayesian Statistics for Beginners

Bayesian Statistics for Beginners PDF Author: Therese M. Donovan
Publisher:
ISBN: 0198841299
Category : Mathematics
Languages : en
Pages : 430

Get Book Here

Book Description
Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.

Statistics for Ecologists Using R and Excel

Statistics for Ecologists Using R and Excel PDF Author: Mark Gardener
Publisher: Pelagic Publishing Ltd
ISBN: 1784271411
Category : Science
Languages : en
Pages : 503

Get Book Here

Book Description
This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Statistical approaches covered include: data exploration; tests for difference – t-test and U-test; correlation – Spearman’s rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal–Wallis test; and multiple regression. Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results. New in this edition: a completely revised chapter on graphics including graph types and their uses, Excel Chart Tools, R graphics commands and producing different chart types in Excel and in R; an expanded range of support material online, including; example data, exercises and additional notes & explanations; a new chapter on basic community statistics, biodiversity and similarity; chapter summaries and end-of-chapter exercises. Praise for the first edition: This book is a superb way in for all those looking at how to design investigations and collect data to support their findings. – Sue Townsend, Biodiversity Learning Manager, Field Studies Council [M]akes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel – Mark Edwards, EcoBlogging A must for anyone getting to grips with data analysis using R and excel. – Amazon 5-star review It has been very easy to follow and will be perfect for anyone. – Amazon 5-star review A solid introduction to working with Excel and R. The writing is clear and informative, the book provides plenty of examples and figures so that each string of code in R or step in Excel is understood by the reader. – Goodreads, 4-star review

R For Dummies

R For Dummies PDF Author: Andrie de Vries
Publisher: John Wiley & Sons
ISBN: 1119963133
Category : Computers
Languages : en
Pages : 470

Get Book Here

Book Description
Master the programming language of choice among statisticians and data analysts worldwide Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter R For Dummies, the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful. Master your R ABCs ? get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables Put data in its place ? get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel Make data dance to your tune ? learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more Visualize it ? learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data Get statistical ? find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests Expand and customize R ? get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes Open the book and find: Help downloading, installing, and configuring R Tips for getting data in and out of R Ways to use data frames and lists to organize data How to manipulate and process data Advice on fitting regression models and ANOVA Helpful hints for working with graphics How to code in R What R mailing lists and forums can do for you

New Statistics with R

New Statistics with R PDF Author: Andy Hector
Publisher: Oxford University Press
ISBN: 0198729057
Category : Mathematics
Languages : en
Pages : 217

Get Book Here

Book Description
An introductory level text covering linear, generalized linear, linear mixed-effects, and generalized mixed models implemented in R and set within a contemporary framework.

Beginner's Guide to Zero-inflated Models with R

Beginner's Guide to Zero-inflated Models with R PDF Author: Alain F. Zuur
Publisher:
ISBN: 9780957174184
Category : Ecology
Languages : en
Pages : 414

Get Book Here

Book Description


Problem Solving with Fortran 90

Problem Solving with Fortran 90 PDF Author: David R. Brooks
Publisher: Springer Science & Business Media
ISBN: 1461219523
Category : Computers
Languages : en
Pages : 712

Get Book Here

Book Description
The author shows how using computers and FORTRAN 95 it is possible to tackle and solve a wide range of problems as they might be encountered in engineering or in the physical sciences.

A Beginner's Guide to GLM and GLMM with R

A Beginner's Guide to GLM and GLMM with R PDF Author: Alain F. Zuur
Publisher:
ISBN: 9780957174139
Category : Ecology
Languages : en
Pages : 256

Get Book Here

Book Description
This book presents Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) based on both frequency-based and Bayesian concepts.