An Introduction to Making Graphs and Maps for Biologists using R

MacLeod, Colin D; MacLeod, Ross

ISBN 10: 1909832081 / ISBN 13: 9781909832084

Editore: Pictish Beast Publicationas, 2022

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Dati bibliografici

• Titolo: An Introduction to Making Graphs and Maps for Biologists using R
• Editore: Pictish Beast Publicationas
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 1909832081
• ISBN 13: 9781909832084
• Rilegatura: Brossura
• Condizione: As New

Descrizione articolo

Riassunto

An Introduction to Making Graphs and Map for Biologists using R provides biologists with a uniquely easy-to-understand introduction to making high quality and informative data visualisations in R. It uses a series of practical exercises based on easy-to-follow flow diagrams to show biologists exactly how to do a variety of key tasks.

These include: 1. Making your first graphs using the GGPlot package in R; 2. Creating graphs to display data from different groups; 3. Creating graphs showing individual data points; 4. Creating other types of graphs; 5. Making maps using the GGPlot package in R.

Together, these represent the key tasks biologists need to be able to create high qualify and informative data visualisastions using R. This means it provides the perfect practical introduction for any biologist interested in learning how to use R to create graphs and maps.

This book is also well-suited to act as a course text for those who wish to teach introductory courses using R to undergraduate, masters or postgraduate students in any biological field. It not only provides a practical guide suitable for accompany the teaching of statistical theory, it also provides off-the-shelf exercises, complete with suitable data sets, that can be used as the basis for practical classes.

From the Back of the Book:

This workbook introduces biologists to the key practical skills they need to create high quality graphs and maps in R. It is aimed both at students who are taking their first courses on data processing, analysis and visualisation and at biologists who wish to teach themselves how to use R. As well as providing a quick-start guide to using R itself, this workbook provides a series of practical exercises based on easy-to-follow flow diagrams that show biologists exactly how to do a variety of key tasks in it. These include:

1.Creating your first graphs in R using the GGPlot package, including making basic graphs, such as frequency distribution histograms, creating high quality graphs suitable for inclusion in presentations and publications, creating different types of graphs from the same data set ,and making graphs that display data from more than data series.

2.Creating graphs to display groups of data using GGPlot, including bar graphs of count data, graphs of summary statistics for one variable with error bars, point graphs of summary statistics for two variables with vertical and horizontal error bars, and box plots.

3.Creatring graphs of individual data points, including scatter plots and line graphs of time series data.

4.Creating other types of graphs from biological data including pie charts and bubble graphs.

5.Creating maps from biological data in R using the GGPlot package.

This is the second book in the Practical Statistics for Biologists Workbooks series. This series aims to fill the gap between learning about statistical theory and learning how to actually use statistics in a practical and biological meaningful way. The focus of this series is, therefore, on the development of practical skills, based on learning appropriate workflows, rather than teaching statistical theory.

The PSLS series of books uses Task-Oriented Learning (TOL) to teach the practical application of research skills to the life sciences. This involves demonstrating how skills can be used in the specific circumstances in which they are likely to be required rather than concentrating on teaching theoretical frameworks or on teaching skills in a generic or abstract manner. By seeing how similar processes are used to achieve a variety of different goals within a specific field, it becomes easier for the reader to understand the general rules behind the practical application of these processes and, therefore, to transfer them to novel situations they may encounter in their own work.