This course takes a hands-on approach towards introducing the theoretical and practical aspects required to undertake rigorous and valid data analysis of multivariate biological datasets using the R environment.
At a glance
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- Dates
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- Please enquire for course dates
- Duration2.5 days
- LocationCranfield campus
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Cost
£800
Course structure
The total length of the course is 2.5 days and consists of several lectures and practical workshops with comprehensive tutorials being delivered throughout the course; covering introduction to R programming and Data Science. The course will take place in a computer lab and delegates will be supported by the tutors and teaching assistants at all times.What you will learn
On successful completion of this course you should be able to:
- Use R syntax and ecosystem to perform data analysis tasks.
- Critically assess the basic principles of different statistical techniques and be able to implement them programmatically,
- Effectively integrate and devise statistical methods into experimental design protocols,
- Conduct initial exploratory data analysis and manipulate the data to meet required specifications using different data pre-processing techniques,
- Apply exploratory data analysis using unsupervised multivariate analysis methods.
Core content
• Introduction to programming in R: data structures in R, functions, control statements and loops.
• Data visualisation and EDA using ggplot2 and interactive visualisation libraries.
• Data pre-treatment and quality control: treating missing values, outliers, data smoothing, data transformation and scaling, looking at data distributions, etc.
• Correlation and linear regression.
• Descriptive statistics and inferential statistics including parametric and non-parametric tests, such as t-test, and analysis of variance (one-way, two-way and mixed ANOVA).
• Unsupervised multivariate analysis: implementing methods such as principal components analysis (PCA), hierarchical cluster analysis (HCA) and k-means to uncover inherent patterns in the dataset to reveal naturally occurring clusters.
Who should attend
This training is suitable for postgraduate students and professionals in Agrifood and life sciences who want to learn best practices for experimental design and data collection, inspection and manipulation and visualisation of biological datasets, statistical analysis using the R environment and interpretation of the results.Accommodation options and prices
This is a non-residential course. If you would like to book accommodation on campus, please contact Mitchell Hall or Cranfield Management Development Centre directly. Further information regarding our accommodation on campus can be .
Alternatively you may wish to make your own arrangements at a nearby hotel.
Location and travel
ÂãÁÄÖ±²¥ is situated in Bedfordshire close to the border with Buckinghamshire. The University is located almost midway between the towns of Bedford and Milton Keynes and is conveniently situated between junctions 13 and 14 of the M1.
London Luton, Stansted and Heathrow airports are 30, 90 and 90 minutes respectively by car, offering superb connections to and from just about anywhere in the world.
Location address
ÂãÁÄÖ±²¥College Road
Cranfield
Bedford
MK43 0AL
Read our Professional development (CPD) booking conditions.