R Programming, Excel & Data Management Books

Our book, An Introduction to R: Data Analysis and Visualisation, is on the way! An Introduction to R is intended as an introduction to using R: The Statistical Programming Language. Regardless of your background or specialty; science, business, engineering, or social science, you’ll find this book a starting point for learning about Data Science, that is, Data Analysis, Data Visualization, and Data Management. This book is not aimed at any particular educational level and should be accessible to anyone who wants to learn R, a powerful and flexible analytical toolbox.

Our book, Beginning R: The Statistical Programming Language, is aimed at helping beginners learn how to use R for data analysis. In Beginning R: The Statistical Programming Language, you’ll learn how to carry out a range of tasks, such as how to use R for importing data, data summary, simple statistical tests, regression, and data visualisation.

In Beginning R: The Statistical Programming Language, you will also learn how to use R for creating custom functions and begin to unlock the secrets of this powerful and flexible Open Source computer language.

Our book, The Essential R Reference, is a topic-led resource book that can help you learn R, as well as being a reference to keep referring to. In The Essential R Reference, you are led to the appropriate R functions by following the task trail to find what you need. Each function is presented with the “essentials”, to make it easier to learn how to use.

The Essential R Reference is a cross between a thesaurus, dictionary and glossary for R, with plenty of examples to help you find your way.

Our book, Managing Data Using Excel, is designed to improve your skills at using Excel as well as managing and dealing with data. In Managing Data Using Excel you will learn how to manipulate and manage data. Key skills you’ll learn in Managing Data Using Excel are; how to arrange your data, how to summarise your data, and how to add graphs and charts.

A key element in Managing Data Using Excel is the use of Pivot Tables. These make managing data easier and more efficient. You’ll learn how to use Pivot Tables for a range of tasks, including data aggregation and summary, and Pivot Charts.

Our book Statistics for Ecologists Using R and Excel is a foundation for learning about statistics. Statistics for Ecologists is designed for beginners using R: The Statistical Programming Language.

You’ll learn how to conduct a range of statistical tests using simple ecological data examples (using Excel and using R). Statistics for Ecologists is designed for undergraduates, giving you skills in using Excel as well as demonstrating how using R can help you in analysis of ecological data.

Our book Community Ecology: Methods of Analysis Using R and Excel, aims to show you how to carry out analyses of ecological community data. In Community Ecology you’ll learn how to carry out a variety of analyses using methods specific to ecological community data.

Community Ecology will show you how to use R (and Excel where appropriate) to carry out methods such as; diversity, similarity, and multivariate analyses (ordination).

If you are looking for the best book to learn R, then we have several options. Our book, Beginning R: The Statistical Programming Language is intended as a general starting point for learning R. It is not specific to any discipline and suitable for anyone wishing to learn R for data analysis. Our book, The Essential R Reference is designed to help you learn R by helping you to find the R functions you need more easily, and to be a resource that you’ll use over and over again.

If you are an ecologist looking for the best book to learn R, then our book, Statistics for Ecologists Using R and Excel is both a primer in R as well as in data analysis and statistical analysis. Statistics for Ecologists is intended as an undergraduate introduction to choosing and using statistics for ecological data. Our book Community Ecology: Methods of Analysis Using R and Excel, can help you learn more advanced analytical methods required for analysis of ecological community data.

So, if you are looking for the Best Book to Learn R, we have a range of options.

Our book, Statistics for Ecologists Using R and Excel covers a range of data analysis methods. Statistics for Ecologists is will give you a foundation in Using R and Excel for various statistical and data analysis methods. You’ll learn how to choose the best statistical test for your ecological data and how to carry out the test using R and Excel.

Basic hypothesis testing and Data analysis methods include:

• Differences tests – t-test and U-test.
• Correlations – Pearson and Spearman’s Rank.
• Associations – Chi Squared tests and Goodness of Fit tests.

More advanced data analysis methods include, ANOVA and Regression. You’ll also learn how to carry out particular ecological statistics, such as diversity and similarity analysis.

In Statistics for Ecologists you will also learn how to use R and Excel to visualise data and results, so that you can produce professional-looking graphs and charts.

Statistics for Ecologists Using R and Excel is intended as a companion for students in ecology and environmental science.

Our book Community Ecology: Methods of analysis using R and Excel is intended to help guide you in your analyses of ecological community data. The book covers a range of methods of analysis of community ecology data, including:

• Diversity (richness, alpha, beta and gamma diversity).
• Rank abundance dominance models (RAD).
• Similarity and dissimilarity.
• Association analysis.
• Multivariate Analysis (Ordination).

In analysis of community ecology, you are dealing with many species, which makes methods of multivariate analysis particularly important. In the book you will learn how to use R: The Statistical Programming Language for various kinds of multivariate analysis (ordination), including:

• Non-metric multidimensional scaling (NMDS).
• Principal Co-ordinates analysis (PCO, PCoA).
• Canonical correspondence analysis (CCA, canoco).
• Redundancy analysis (RDA).

Other methods of multivariate analysis used in community ecology are also introduced in the book.

Community Ecology is designed to support your studies in ecology and give you the tools you need to analyse your community data.