ST2304 Statistisk modellering for biologer/bioteknologer (våren 2024)

This page contains the timetable and links to all of the material (modules, exercises etc.). There will only be small changes from previous years: the course material (lecture notes etc.) from last year are here.

For å få full tilgang til emnet, så må du

  • ha en aktiv NTNU-brukerkonto
  • ha betalt semesteravgift for våren 2024
  • være undervisningsmeldt i emnet (sjekk på StudentWeb)

Kontakt faglærer Bert van der Veen hvis du fremdeles ikke har tilgang.

To hand in exercises – go to Blackboard. Emnet går i Blackboard Vår 2024.

We have set up a discussion forum, so you can use that to ask questions (and to answer them too). You can post anonymously.

A zoom room will be active during all sessions at this link, to answer questions you might have if you are unable to attend in person.

The exam for last year is here, and here are the solutions

Timetable

Starts Wednesday 10th January at 10:15.

  • Wednesday 10:15 - 12:00
  • Thursday 16:15 - 18:00
  • Friday 12:15 - 14:00

All sessions will take place in R2. All materials will be found at this web link - just click on the correct folder for the lecture week https://www.math.ntnu.no/emner/ST2304/2024v/ (Note: this is not set up yet)

None of these books is perfect for this course, or is necessary to buy. If you want only one, Hector is probably best unless you are happy to read something a bit more technical (= has lots more equations), in which case Dunn & Smyth is good.

New Statistics with R - Hector: a useful practical book, it covers the material well, but not deeply.

The Analysis of Biological Data - Whitlock & Schluter - covers a lot of the more basic ideas in detail.

Generalized Linear Models With Examples in R - Dunn & Smyth This is mathematically a bit more advanced, but is fine if you are comfortable reading equations.

Course Material

There are a couple of questions we would like you to answer, to help the course run better, here: please answer this survey.

We will repeat these on the first Wednesday during the introduction lecture.

Week 2: Introduction (week beginning January 8th)

Taskcard link (this will be explained)

Week 3: Maximum Likelihood (week beginning January 15th)

Starting this week you just go through the modules, so everything is pre-written and pre-recorded.

Videos (these are linked to in the module)

Week 4: Uncertainty in Maximum Likelihood (week beginning January 24th)

This week we start exercises, wth Exercise 1. These should be done in groups, and handed in on Blackboard.

Week 5: The Normal Distribution (week beginning January 29th)

Week 6: Regression (week beginning February 5th)

Week 7: Regression (week beginning February 12th)

Week 8: Regression (week beginning February 19th)

Week 9: Categorical Variables (aka ANOVA) (week beginning February 26th)

Week 10: Interactions between Categorical Variables (week beginning March 4th)

Week 11: Model Selection (week beginning March 11th)

This week's module is split into 3 parts, because it was getting a bit long.

In addition we have a couple of scripts that might help you when running the problems in R:

Week 12: Full Analyses (week beginning March 18th)

Because it is Easter next week, this will be a bit different. We want you to look at the whole process of data analysis, i.e. use all the parts you have been learning over the last few weeks to answer some biological questions.

We only expect you to answer one of these, but we will be happy if you try both. There are two ways to answer them: some exam-style questions (for those of you looking ahead), and a more free-form "try to do the analysis on your own". For those of you taking the continuation exam, note that this will probably be an oral exam, so we will ask you to do an analysis like this, and discuss in in the exam.

The deadline for handing in is the end of April 5th, i.e. you get an extra week, during which you can do something more fun.

Week 14: GLMs (week beginning April 1st)

Week 15: Binomial Generalised Linear Models (week beginning 8th April)

Week 16: Poisson Generalised Linear Models (week beginning 15th April)

2024-04-16, Bert van der Veen