Data Analysis in R

Overview

Data Analysis in R helps you analyse data but also to understand and critically evaluate scientific literature, design your own experiments and report your results.

Learning Data Analysis is important…

Reproducible data management, handling, wrangling, modelling and visualisation underpin the scientific process. But they are also amongst the most in-demand hard skills.

… and takes time …

Part of the reason that these skills are in-demand is that they take time –practice – to learn in the same way that playing an instrument, speaking another language or playing a sport take time and practice. They are skills you develop more than facts you memorise. You will make a lot of mistakes.

… but can be great fun …

There is a lot of problem solving which is engaging work because there’s always something to ‘chase’. You may be able to concentrate on coding for much longer than on writing or reading because it is such an active learning process. You’ll create impressive looking figures, which you can reproduce on a different dataset in moments, reveal exciting biological insights through data visualisation and analysis and learn whole world of ‘techy’ tricks you had no idea you’d be able to do!

The time and effort you put in to learning “Data Analysis in R” will reward you no matter how you evaluate yourself. You will be able to:

better and/or more quickly design and analyse scientific investigations for modules and projects in which in turn will allow you to perform better in assessments.
evaluate and interpret the data analysis in papers
access a wide range of careers

… and there’s help!

There is a book to support the Data Analysis in R content in your degree: Computational Analysis for Bioscientists

What is this site for?

All the Data Analysis in R teaching is on the VLE so why is this site useful? Well, perhaps more than any other material, you will want to refer back when applying your skills throughout your degree. This site collects everything together and is searchable. The search icon is on the top right.

Make a suggestion

Those with GitHub accounts can make a suggestion dorrectly from a site webpage. When you find errors – from simple typos to more troublesome issues – or want to make a suggestion, please use the “Make a suggestion” link on the right. This will open an “issue” on github (where the site is hosted) where you can let me know about the error or suggestion.

There is absolutely no requirement to use Git or GitHub in the BABS modules.

--- title: "Data Analysis in R" toc: true toc-location: right --- # Overview Data Analysis in R helps you analyse data but also to understand and critically evaluate scientific literature, design your own experiments and report your results. ## Learning Data Analysis is important... Reproducible data management, handling, wrangling, modelling and visualisation underpin the scientific process. But they are also amongst the most in-demand hard skills. ## ... and takes time ... Part of the reason that these skills are in-demand is that they take time –practice – to learn in the same way that playing an instrument, speaking another language or playing a sport take time and practice. They are skills you develop more than facts you memorise. You will make a lot of mistakes. ## ... but can be great fun ... There is a lot of problem solving which is engaging work because there's always something to 'chase'. You may be able to concentrate on coding for much longer than on writing or reading because it is such an active learning process. You'll create impressive looking figures, which you can reproduce on a different dataset in moments, reveal exciting biological insights through data visualisation and analysis and learn whole world of 'techy' tricks you had no idea you'd be able to do! The time and effort you put in to learning "Data Analysis in R" **will** reward you no matter how you evaluate yourself. You will be able to: - better and/or more quickly design and analyse scientific investigations for modules and projects in which in turn will allow you to perform better in assessments. - evaluate and interpret the data analysis in papers - access a wide range of careers ## ... and there's help! There is a book to support the Data Analysis in R content in your degree: [Computational Analysis for Bioscientists](https://3mmarand.github.io/comp4biosci/) ## What is this site for? All the Data Analysis in R teaching is on the VLE so why is this site useful? Well, perhaps more than any other material, you will want to refer back when applying your skills throughout your degree. This site collects everything together and is searchable. The search icon is on the top right. ## Make a suggestion Those with [GitHub](https://docs.github.com/en/get-started/start-your-journey/about-github-and-git#where-do-i-start) accounts can make a suggestion dorrectly from a site webpage. When you find errors – from simple typos to more troublesome issues – or want to make a suggestion, please use the "Make a suggestion" link on the right. This will open an "issue" on github (where the site is hosted) where you can let me know about the error or suggestion. **There is absolutely no requirement to use Git or GitHub in the BABS modules**.