๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Statistics for Ecologists Using R and Excel: Data Collection, Exploration, Analysis and Presentation (Data in the Wild)

โœ Scribed by Mark Gardener


Publisher
Pelagic Publishing
Year
2017
Tongue
English
Leaves
418
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Synopsis


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


๐Ÿ“œ SIMILAR VOLUMES


Statistics for Ecologists Using R and Ex
โœ Mark Gardener ๐Ÿ“‚ Library ๐Ÿ“… 2017 ๐Ÿ› Pelagic Publishing ๐ŸŒ English

<p><span>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 carr

Statistics for Ecologists Using R and Ex
โœ Mark Gardener ๐Ÿ“‚ Library ๐Ÿ“… 2017 ๐Ÿ› Pelagic Publishing ๐ŸŒ English

<span><span>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 c

Statistics and Data Analysis for Microar
โœ Sorin Draghici ๐Ÿ“‚ Library ๐Ÿ“… 2011 ๐Ÿ› Chapman and Hall/CRC ๐ŸŒ English

<P>Richly illustrated in color, <STRONG>Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition</STRONG> provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details

Using R for Data Management, Statistical
โœ Nicholas J. Horton, Ken Kleinman ๐Ÿ“‚ Library ๐Ÿ“… 2010 ๐Ÿ› CRC Press ๐ŸŒ English

Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate

Using R for Data Management, Statistical
โœ Nicholas J. Horton, Ken Kleinman ๐Ÿ“‚ Library ๐Ÿ“… 2010 ๐Ÿ› CRC ๐ŸŒ English

Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate