Advanced Methodology

URL study guide

https://studiegids.vu.nl/en/courses/2024-2025/B_ADVANMETH

Course Objective

The student understands the basic principles underlying modern statistical techniques, is able to apply them in Python and interpret the results. Main learning objectives:
•Understand statistics from a model fitting perspective
•Understand how to fit contemporary models to data
•Know how to implement model fitting in python

Course Content

An introduction to statistical methods common in modern experimental research. All techniques will be applied to experimental or simulated data in Python. The topics covered in this course are:
• Basic statistical principles (generative models, estimation, testing, experimental design)
• Linear regression (simple and multiple regression)
• Model fitting, model diagnostics and model comparison
• Analysis of variance (one-way, two-way, interaction)
• Repeated-measure ANOVA
• Linear Mixed models
• Generalized linear models (logistic regression and Poisson regression)

Teaching Methods

Lectures and practical computer assignments using jupyter notebooks

Method of Assessment

Weekly reports on data analyses using the Python

Literature

Lecture slides, notes, jupyter notebooks

Custom Course Registration

VUnet or on canvas

Entry Requirements

• Basic mathematics and linear algebra
• Basic statistics concepts (sampling distributions, hypothesis testing, confidence intervals)
• Familiarity with common probability distributions
• Basic programming skills

Explanation Canvas

All information will be available via Canvas