András: "Please formulate an explanation why molecular biology PhD students and postdocs would benefit from a course on Generalised Linear Models (GLM-s). The course discusses Binomial GLMs aka logistic regression, Poisson and Quasi-Poisson GLMs and "classical" least squares as a special case. The explanation shall be brief, appropriate for people with little time to read emails, and it should have a professional but upbeat tone as the purpose of this explanation is to motivate the target audience to sign up."

Claude 4.6: "If you've ever wrestled with count data, proportions, or binary outcomes in R — and forced them into a t-test or ANOVA anyway — this course is for you.

Generalised Linear Models (GLMs) give you the right statistical tool for the data you actually collect in molecular biology:

• 🧬 Logistic regression — for binary outcomes (e.g. cell survival, mutation presence/absence)
• 🔢 Poisson/Quasi-Poisson GLMs — for count data (e.g. read counts, colony counts, foci per cell)
• 📐 Least squares as a special case — finally understand why linear regression works when it does

No more shoehorning non-normal data into the wrong model. GLMs let you analyse your data honestly, report results rigorously, and hold your own in peer review.

The course is hands-on, biology-focused, and designed for people who didn't sign up for a statistics degree — but need to do statistics well."

If you were convinced by the LLM's sales pitch, here are some details:

Date/Time: Tuesday 5th May, from 09:00 to 13:00.

Mandatory pre-requisite: Good basic statistics skills.
Recommended but not essential: Familiarity with least-squares regression techniques.

Cost: Free of charge.

How to register: 
First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly.
1) Check your calendar!
2) Ask your PI.
3) Go to the Training schedule page https://training.vbcf.ac.at/training/schedule.php , click on the "Register" button for the course and fill out the little form.