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Quantitative Research Methods
Quantitative Research Methods

Getting started

  • Quick start
  • For students
  • The course at a glance
  • Python environment

Materials

  • Lecture slides
  • Lab notebooks
    • Chapter 0 — Precourse Refresher
    • Chapter 0b — Precourse Toolkit
    • Chapter 1 — Introduction
    • Chapter 2 — Statistical Learning
    • Chapter 3 — Linear Regression
    • Chapter 4 — Classification
    • Chapter 5 — Resampling Methods
    • Chapter 6 — Model Selection and Regularisation
    • Chapter 7 — Moving Beyond Linearity
    • Chapter 8 — Tree-Based Methods
    • Chapter 9 — Support Vector Machines
    • Chapter 10 — Deep Learning
    • Chapter 11 — Survival Analysis
    • Chapter 12 — Unsupervised Learning
    • Chapter 13 — Multiple Testing
  • Mock exams
  • Datasets
  • Advanced modules
    • Advanced Module A1 — Randomised Controlled Trials
    • Advanced Module A2 — Explainable AI with Shapley Values
    • Advanced Module A3 — Conformal Prediction
    • Advanced Module A4 — GLMs and Splines
  • Short projects

Teaching

  • Teaching it

Project

  • Repository layout
  • Building this documentation
  • Citation & licence
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Copyright © 2026, Christoph Weisser (HSBI). Based on ISLP (Springer, 2023)
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