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R Package for Statistical Analysis: An Introduction
Domain: A1 Knowledge base

TACE: A - Acquisition

Due to the Covid-19 outbreak, all face to face training at the Doctoral Academy has been postponed for the foreseeable future.

This session will be run as a Webinar - to book a place click here

Listed below is a selection of external learning resources related to this subject that you may find useful.

Learning R
R Statistics Essential Training
Data Wrangling in R
Cleaning Bad Data in R
R for Excel Users
Data Science: Foundations Using R
The R Programming Environment
Statistics and R
Introduction to R for Data science
Principles of Machine Learning: R Edition
Data Science: R Basics

For more information on identifying and accessing online learning resources click here
For more information on replacement learning events such as webinars and retreats click here


Format: IT
Suitable for: All

R is one of the best statistical packages available. It also happens to be Open Source software - free to download (via and very well documented. R comes with a base package of standard statistical tasks but other packages (including interactive ones) are easily downloaded from the thousands which are available.

Amongst its strengths are:
* numerous standard and state-of-the-art statistical procedures including those dealing with non-numerical data
* comprehensive documentation – from beginners’ to technical level and including examples which you can paste in, run and modify for your own purposes
* many built-in data sets for developing methods
* excellent graphics

This beginners’ session will cover:
* loading data sets into R
* navigating some basic commands for summarizing and plotting data
* running basic statistical procedures, tests, etc.
* downloading/accessing specialist R packages

R Package for Statistical Analysis: Intermediate is also available

Additional coaching opportunities are available via weekly data clinics.

More information on this subject may be available on the range of online learning resources such as Linkedin Learning