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Purpose

Enables Life Scientists to Effectively and Rapidly Analyse Their Data Using the R Software Package

 

Participants Learn How To:

  • Operate R using variables, functions, indexing and packages.
  • Import their own data regardless of size or format.
  • Perform standard statistical tests on large data-sets.
  • Produce plots and highlight specific data-points.
  • Begin programming in R using the apply functions.
  • Use split-combine-apply strategies for calculations and data manipulation.
  • Begin to adopt a bioinformatician’s perspective.

 

Our Teaching Approach:

  • Emphasises hands-on exercises – “Learning-by-doing” reinforces participants’ understanding.
  • Uses relevant examples – Biological data-sets engage participants and help them to relate the material to their own work.
  • Provides case studies – In-depth examples reinforce the power and simplicity of data analysis using R.
  • Creates an informal atmosphere that motivates life scientists to analyse their own data.

 

Science Craft’s Distinctive Advantage:

  • A reference book written for the specific needs of life scientists who do not have programming experience or knowledge of R.
  • Instructors are life scientists with both laboratory and computational research experience using diverse applications of R.
  • This stand-alone course can be supplemented with the Data Visualization course to provide students with a comprehensive grounding in producing elegant graphics and statistics from raw data.

 

Course Details
Duration: 3 full days
Maximum Capacity: 12 participants with one instructor
Instructors: Dr. Rick Scavetta

Feedback

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Very structured and informative workshop.

Very efficient, well-structured and motivating introduction to R language.

I learnt a lot more than I expected to, which is great.

Very well-structured and very helpful workshop.

It was worth taking the workshop.

  Workshop Description   Table of Contents   Feedback Summary

 

 


The Data Analysis workshop teaches students how to use the R statistics package with R-Studio for efficient data management.