R Programming & Data Science Short Courses

Description:

Introduction to Statistics Using R and RStudio – Online

Discover the power of RStudio for data analysis and statistics in this practical, online workshop.

Whether you’re an early-career researcher, a PhD student or academic looking to broaden your methods, or a professional data analyst interested in robust statistical tooling, this course provides you with a comprehensive understanding of how to use RStudio for data wrangling, visualisation, and statistical modelling, allowing you to move confidently toward more advanced analysis.

Introduction to Generalised Linear Models in R - Online

Develop your skills in Generalised Linear Models (GLMs) using R and learn how to handle more complex forms of data analysis.

This two-day course offers a practical introduction to GLMs, equipping you with the knowledge and confidence to apply these models effectively. Moving beyond ordinary linear regression, GLMs allow you to model a wide range of data types, including binary, ordinal, categorical, and count-based outcomes.

Through expert led online instruction and hands-on coding exercises, you'll gain a solid understanding of how and when to use GLMs and how to interpret and evaluate your results in a meaningful way.

Introduction to Multilevel and Mixed Effects Models using R - Online

Introduction:

Learn how to analyse hierarchical data structures using R.

R is a major tool in modern data analysis and statistics, used extensively in academic research as well as by data analysts in the public and private sectors. Its flexibility, comprehensive ecosystem of packages, and active community have made it highly suited for all aspects of data analysis.

This two-day online course offers a thorough, hands-on introduction to working with R and RStudio, which is the most widely used integrated development environment for R. By participating, you’ll gain the foundational skills needed to handle real-world datasets, develop reproducible analytical workflows, create effective data visualisations, and conduct a wide range of common statistical techniques.

Whether you’re an early-career researcher, an academic looking to broaden your methods, or a professional data analyst interested in robust statistical tooling, this course equips you to move confidently toward more advanced analysis.

Introduction to Bayesian Data Analysis using R - Online

Introduction:

Bayesian methods are becoming an increasingly popular approach to data analysis across a wide range of research fields. They offer a flexible and structured framework for statistical inference, differing fundamentally from traditional (frequentist) methods. However, many researchers have limited opportunities to learn the core principles of Bayesian inference, making it challenging to apply these techniques effectively.

Cost:

£360 - £480

Website and registration:

Register for this course

Region:

East Midlands

Keywords:

Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, Research Management and Impact, Research Skills, Communication and Dissemination, Rstat, Coding in R, Data Cleansing, Data Preprocessing, ggplot2, RMarkdown, Quarto, Binary Logistic Regression, Ordinal Logistic Regression, Poisson Regression, Negative Binomial Regression, Zero-Inflated Models, Bayesian Data

Related publications and presentations from our eprints archive:

Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
Research Management and Impact
Research Skills, Communication and Dissemination

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