R Stats

Duration: 3 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

On this three-day course, you will gain a solid introduction to Bayesian methods, both theoretically and practically. 

We will teach the fundamental concepts of Bayesian inference and Bayesian modelling, including how Bayesian methods differ from their classical statistics counterparts, and show how to do Bayesian data analysis in practice in R. 

This course is aimed at anyone who is interested to learn and apply Bayesian data analysis in any area of science, including the social sciences, life sciences, physical sciences.

No prior experience or familiarity with Bayesian statistics is required.

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.

Duration: 2 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

In this two-day course, you will gain a comprehensive introduction to data visualization in R using ggplot.

We will cover all the major data visualization techniques and use them to explore and illustrate the major patterns in data.  

This course is aimed at anyone who is interested in doing data visualization using R.

Data visualization is a major part of data science and statistical data analysis, and R is the most widely used program for data science and statistics.

Data visualization using R is widely used throughout academic scientific research, as well as widely throughout the public and private sectors. 

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.

Duration: 2 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

On this two-day course, you will gain a comprehensive practical introduction to data wrangling using R. In particular, we focus on tools provided by R's `tidyverse`, including `dplyr`, `tidyr`, `purrr`, etc.

Data wrangling is the art of taking raw and messy data and formating and cleaning it so that data analysis and visualization etc may be performed on it.

Done poorly, it can be a time consuming, labourious, and error-prone.

Fortunately, the tools provided by R's `tidyverse` allow us to do data wrangling in a fast, efficient, and high-level manner, which can have dramatic consequence for ease and speed with which we analyse data.  

This course is aimed at anyone who is involved in real world data analysis, where the raw data is messy and complex.

Data analysis of this kind is practiced widely throughout academic scientific research, as well as widely throughout the public and private sectors. 

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.

Duration: 2 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

In this two-day course, you will obtain a comprehensive practical and theoretical introduction to generalized linear models using R.

Generalized linear models are generalizations of linear regression models for situations where the outcome variable is, for example, a binary, or ordinal, or count variable, etc.  

This course is aimed at anyone who is interested in advanced statistical modelling as it is practiced widely throughout academic scientific research, as well as widely throughout the public and private sectors. 

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.

Duration: 2 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

On this two-day course, you will obtain a practical and theoretical introduction to doing multilevel or mixed-effects regression modelling using R.

We will particularly focus on multilevel or mixed effects linear models, which are very widely used throughout the social and biological sciences.

We will use the popular `lme4` R package, as well as the acclaimed `brms` R package for Bayesian analyses. 

This course is aimed at scientific researchers and data analysts who are interested in advancing their level of statistical knowledge and techniques beyond standard regression analysis to regression methods that are suitable for modelling clustered or hierarchical data sets, which are very common in the social and biological sciences.  

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.

Duration: 2 day online course

Course Module: Non-accredited

Level: CPD, Advanced / Professional

In this two day course, you will obtain a comprehensive introduction to R and RStudio and how it can be used for data science and statistics in an academic or professional setting.  

This course is aimed at anyone who is interested in using R for data science or statistics. R is widely used in all areas of academic scientific research, and also widely throughout the public, and private sector. 

You can sign up for this course at any point within the live period until 3 working days prior to the course commencing.