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Intensive R Course (4 Days) 2017

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Course Information

R Intensive

R: a powerful tool for statistical analysis and data visualisation

R is a free software programming language and software environment for statistical computing and graphics. R is used by some of the largest organisations in the world and many more statisticians and data miners for developing statistical software and data analysis.

Course Overview: This four-day course will give you the skills to access data analysis techniques, create striking and unique data visualisations, and get better results faster. You will learn the basic concepts of R and how to benefit by using this powerful analysis tool before gaining the skills to manage large-scale data sets independently and in a proficient manner.

Each day you will have access to computers but you may wish to bring your own laptop to workshops so you can use R in a familiar context.

Course Options: This course is also available as a beginner’s two-day course or an advanced two-day course.

Attendance to individual days can be arranged upon request.

Dates: Monday 11th September 2017 - Thursday 14th September 2017 (four days) 

Times: 9am-5pm (includes refreshment and lunch breaks)

The price is inclusive of VAT

Course Code


Course Dates

11th September 2017 – 14th September 2017

Course Leader

Golnaz Shahtahmassebi

Course Fee

Course Description

Entry Requirements: No prior knowledge or experience of R is required. Workshops are designed for people who want to learn R and a basic understanding of statistics would be useful but not essential. Each workshop has been designed to take you through the basics of R right the way to an advanced level. Attendees will learn how to:

  • Produce professional graphics
  • Customise R’s core analytical capabilities for your own purposes
  • To visualise sequencing or related kinds of data
  • To integrate R into your Next Generation Sequencing (NGS) workflow.


Day One: Start using R for statistical analysis

Learn about:

  • R’s basic concepts and capabilities to suit your personal requirements
  • Components including the R environment
  • Data objects and variations of data sets
  • Working with data generating standard graphics

Learn how to:

  • Produce summary statistics simply
  • Carry out analysis of variance or regression analysis, a statistical process for estimating the relationships among variables
  • Calculate sample size and the power of a statistical test

You will gain:

  • An insight to R environment, language and tools
  • Basic skills in R such as installing R and using R help
  • Handling data and managing large data sets
  • Performing simple statistical analysis in order to communicate the largest amount of information simply


Day Two: Explore R graphics in depth

Learn about:

  • The powerful core graphical capabilities of R
  • Explore the advanced capabilities associated with the lattice and googleVis packages
  • Lattice graphics in R to make use of grid graphics

Learn how to:

  • Skills for visualising data and producing professional graphics in R
  • Customise R base graphics within the graphics package of R systems
  • Use the ggplot2 package, which provides a powerful model of graphics facilitating the production of complex multi-layered graphics


Day Three: Advanced R skills

Learn about:

  • Looping, conditional expressions which perform different computations or actions
  • How to write your own functions and three main parts: input, relationship, output
  • How to perform advanced statistical analyses such as: logistic regression, survival analysis and Bayesian analyses in R using packages including MCMCpack and coda

You will be able to:

  • Define functions, how to define variables and how to return variables through Writing of your own R functions
  • Use R for performing advanced statistical analysis


Day Four: Visualising Genomics Data with R

You will learn:  

  • How to visualise and summarise data generated by Next Generation Sequencing (NGS) platforms
  • How to use some helpful packages for handling sequence data (e.g., ape, for phylogenetic analysis)

We will also:

  • Offer a gentle introduction to the bioconductor repository, using tools for the analysis and comprehension of high-throughput genomic data, a discipline in genetics that brings together genetic material from multiple sources to create sequences

You will gain:

  • Skills for visualising experimental data
  • An approach to inspecting and interpreting genomic data
  • The skills required to analyse the Next Generation Sequencing (NGS) and other large-scale data sets independently and in a proficient manner


Course Leader Profile: Dr Golnaz Shahtahmassebi

Dr Golnaz Shahtahmassebi is a lecturer in statistics and an applied statistician at Nottingham Trent University. She uses R extensively in her research in statistical and computational methods related to life sciences including medicine, sport, and physics. She has delivered training and support sessions to her students as a part of courses in Mathematics and Statistics at Nottingham Trent and Plymouth Universities.

Additional Information:

For NTU Staff/Student discount please contact

Email: CST Short Courses