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Data Analysis with R statistical Software: A Guidebook for Scientists
The ability to understand, use and interpret statistics is one of the most empowering skills that a scientist can possess, because it enables the researcher to address any kind of scientific question in a rigorous and quantitative manner. When using statistics, scientists need to be sure that they are collecting the right sort of data in well-designed experiments, using the most appropriate statistical tests, and interpreting the results properly. Statistical analysis does not necessarily come easily to many scientists, but it is an increasingly important and useful part of the toolkit of techniques that are available for understanding the world about us. R is a very powerful statistical software package that will enable you to analyse more or less any dataset. This concise guide is designed to help you quickly to become familiar with R and to explore its potential as a powerful tool for analysing your data, whatever your field of research.
285 pages, Kindle Edition
First published August 31, 2015
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October 3, 2025
I read the spiral bound version of this which for me worked much better as it allows for tabbing, underlining and note making within it.
This is a pretty comprehensive guide on how to actually use R software from the basics of importing your data, checking it, and creating graphs, to implementing complex statistical analysis. It doesn't tell you what you need to do and when in terms of which test is most appropriate but it tells you how to get R to do, which is probably the hardest part of any data analysis nowadays (or it certainly is for those of us who grew up with excel!). It is written in normal language and clearly lays out how you need to draft code in R (this is what the instructions you type in are called, still don't like it) as well as tips and tricks for how to keep a record of what you've done etc. And there are some pleasing humorous little bits in there too just to help you get through the process. Even if it doesn't cover the exact test or process you need it'll be a huge help (can confirm from experience). I cannot recommend this highly enough.
This is a pretty comprehensive guide on how to actually use R software from the basics of importing your data, checking it, and creating graphs, to implementing complex statistical analysis. It doesn't tell you what you need to do and when in terms of which test is most appropriate but it tells you how to get R to do, which is probably the hardest part of any data analysis nowadays (or it certainly is for those of us who grew up with excel!). It is written in normal language and clearly lays out how you need to draft code in R (this is what the instructions you type in are called, still don't like it) as well as tips and tricks for how to keep a record of what you've done etc. And there are some pleasing humorous little bits in there too just to help you get through the process. Even if it doesn't cover the exact test or process you need it'll be a huge help (can confirm from experience). I cannot recommend this highly enough.
Displaying 1 of 1 review