Nowadays, there are so many statistical techniques available. It can be a daunting task to decide which method to apply to your own data. In our experience, there are two steps involved in this process. First, you need to find a statistical tool that is potentially useful for your data analysis. And then you apply this method to your own data. The latter step requires detailed knowledge of the method. You can get this by reading a book, attending a course, searching the internet, reading help files, etc. This can be a painful and slow process, but at least you are progressing and learning. That is provided you have selected the correct approach in step 1! How do you know that you have selected the correct approach? This is where you speak to a statistician or a colleague. They will advise you to look at a specific statistical method, book, or paper. But not everyone has access to a good statistician or knowledgeable colleague.
Would it not be nice to watch an entertaining, short, non-technical, live video stream in which two experts (Dr. Alain F. Zuur and Dr. Elena N. Ieno) discuss the general concepts of a specific statistical technique? Knowing that a specific statistical technique exists, learning the general concepts, and seeing an example of how it is applied may save you a lot of time!
Once in a while, we will run a free live Zoom session in which we discuss the general concepts of a specific statistical method. During the session, you can interact via a chatbox.
The following free live Zoom sessions are scheduled.
Zero-inflated GLM and GLMM for the analysis of count data. Free live seminar using Zoom on Monday 6 November 2023; 14.00- 16.30 UK time.
- We start with a brief revision of the Poisson, negative binomial and Bernoulli distributions. We then discuss how these distributions are used in Poisson, negative binomial and Bernoulli generalised linear models (GLM) and generalised linear mixed-effects models (GLMM). We will use two case study chapters to show how one can decide whether a GLM(M) or generalised additive mixed effects model (GAMM) can cope with a data set that contains an excessive number of zeros. The first case study is using count data and the second case study continuous data. In both analyses, we will extend the GLM(M)s and GAM(M)s toward zero-inflated models.
Data exploration and visualisation. Free live seminar using Zoom. 22 April 2024.
- A description will follow.
Join one of our free online seminars
- Due to the UK's Data Protection Act, we will not record seminars. If we were to record the seminar, and if you ask a question, then your name becomes visible in the video. And that has legal consequences if we were to upload that. Hence the reason we will not record the seminar. You are free to use screen recording software yourself to record the seminar.
- All online seminars are non-mathematical presentations.
- We will use Zoom webinar. Once 500 participants have joined the webinar, Zoom will automatically block the entrance. We will start the Zoom webinar at 13.45; just join early to avoid a closed door.
- If you register for a seminar but cannot attend, please cancel (use the 'Cancel' button above). Failure to cancel may result in not being invited to a future seminar.
- We will email you the Zoom link for the meeting 2 days before the start of the seminar.