Digital Method of the Month: Focus on Statistical Methods Part 2 - Linear Modelling
Online
This is the second meeting of the three-part series on Statistics and will focus on linear modelling. Linear modelling can help you understand and predict the behaviour of complex systems or analyse a phenomenon/trend. Part one will focus on an introduction to statistics and on the difference between descriptive and inferential statistics and part three will focus on simulation.
Have you seen a presentation on digital research methods and wondered if they are applicable to your work? Are you interested in learning new digital skills but unsure where to start?
This is the right place for you!
The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research.
Each month we select a method, and we have an honest and practical discussion on what it takes to learn and master it. How much time will it take to get the basics? What are the software options available? What are the most common pitfalls? Where can you find more info on the subject? Etc...
Join us to discuss the main techniques and technologies available, and their limitations and potentials.
This is a beginner-level event, and no previous knowledge of the method is required.
To attend this event, you will have to join the associated Microsoft Teams group. The link to join the group will be sent to the attendees prior to the course start date, so please make sure to do so in advance.
This Digital Method of the Month will be taught by Fang Jackson-Yang and Rhys Davies.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
If you're interested in other training on statistics, have a look at the following:
- Introduction to Machine Learning with Python
- Null Hypothesis Testing in R
- Introduction to Bayesian Statistics
- A Gentle Introduction to Causal Inference
- Regression and Mixed Effects Modelling
