Understanding statistics and experimental design

BIO-449

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Course summary

Course Schedule

Lectures take place every Monday from 14:15 to 16:00, beginning on September 8, in MA A1 10. The lectures are given on campus, but recordings of last year’s lectures will also be available on Moodle. Exercise sessions are scheduled every Monday from 16:15 to 18:00, beginning on September 29, also in MA A1 10.

You can ask questions in the Moodle forum as well as during the exercise sessions, which are held on campus.

Textbook reference: Understanding Statistics and Experimental Design (Link, Free access for everyone)

Exam questions (2020): Link

Exam date: 14th January 2026

TAs:
Ece Yatikci (ece.yatikci@epfl.ch)
Sandali Liyanagoonawardena (sandali.liyanagoonawardena@epfl.ch)


Exam

Important Announcement

  • Date: 14th of January 2026
  • Time: 10:15 - 12:15
  • Location: CM 1 121
  • Please bring a white corrector and a blue/black pen
  • No calculators or other materials allowed during the exam



Week 1: September 8

This week's lecture: 14.15-16.00
This week's exercise: no exercise!

Slides:
Lecture 1

Lecture Recording: Link to recorded lecture 

Book Chapter: Basic Probability Theory

Interesting references:



September 15 & 22

Important Announcement
  • No class on September 15 (cancelled).
  • No class on September 22 (public holiday).
  • Next session: September 29 → Chapter 2 will be covered then.

If you have questions about the first session, please post them on the forum or email the TAs so they can assist you.


Week 2: September 29

This week's lecture: 14.15-16.00
This week's exercise: 16.15-18.00

Lecture Slides: Lecture 2

Exercise questions: Week 2 - Exercises, z_table

Exercise solutions: Week 2 - Solutions

Lecture Recording: Link to the recorded lecture

Book Chapter: Experimental Design and the Basics of Statistics: Signal Detection Theory (SDT)



Week 3: October 6th

This week's lecture: 14.15-16.00
This week's exercise: 16.15-18.00

Lecture Slides: Lecture 3

Lecture Recording: Link to the recorded lecture

Exercise questions: Week 3 - Exercises, t-table

Exercise Solutions: Week 3 - Solutions



Week 4: 16 October


This week's lecture: 14.15-16.00
This week's exercise: 16.15-18.00

Lecture Slides: same as Week 3

Lecture Recording: Recording


Week 5: 27 October

This week's lecture: 14.15-16.00

This week's exercise: 16.15-18.00

Important: Slide 38 - Assumptions for t-test is updated! 

Lecture Slides: Lecture 4

Lecture Recording: Link to the recorded lecture

Exercise questions: Week 5 - Exercises, Jostmann et al., (2009), Gpower, Wilcoxon Table

Exercise solutions : Week 5 - Exercise Solutions, Question 3 Solution

Book Chapter: Experimental Design: Model Fits, Power, and Complex Designs

Link to the Survey: https://forms.gle/5LRfVASMdv7kzgqe9 



Week 6: November 3

Lecture Slides: Lecture5, Lecture6

Lecture Recording: Link to recorded lecture

Exercise questions: Ex. 1 from Week 5; Week 6 - Exercises

Exercise answers: Week 6 - Solutions

Book chapter: The multiple testing problem




Week 7: November 10

Lecture Slides: Lecture 6 (same as in Week 6), Lecture 7

Lecture Recording: Link to recorded lecture

Exercise questions: Week 7 - Exercises

Exercise solutions: Week 7 - Solutions

Book chapter: ANOVA

Critical F value table: link to table


Week 8: November 17

Important Announcement

  • No class on 17th November 2025 (cancelled).




Week 9: November 24

Lecture Slides: Lecture 7, Lecture 8, PCA

Exercise solutions: Week 8 - Solutions 1, Week 8 - Solutions 2

Exercise questions: Week 8 - Exercise 1, Week 8 -  E1 data, Week 8 - Exercise 2, Week 8 - E2 data

Lecture Recording: Link to the recorded lecture

Book Chapter: Experimental Design: Model Fits, Power, and Complex Designs




Week 10: December 1st

Lecture Slides: PCA, Bayes, Test Validity

Exercise questions: Week 10 - Exercises

Exercise solutions: Week 10 - Solutions

Lecture Recording: No recording available



Week 11: December 8th

Lecture Slides: Lecture 9, Lecture 10, Lecture 9 - updated

Exercise questions: No exercise this week

Lecture Recording: Link to the recorded lecture 9, Linked to the recorded lecture 10

Book Chapter: Meta-analysis



Week 12: December 15th

Lecture Slides: Lecture 11, Lecture 12

Exercise questions: No exercises this week

Lecture Recording: Link to the recorded lecture, Link to the recorded lecture p2

Book Chapter: Magnitude of Excess Success



Summary: Jan 8th

Slides: Summary

There is no recording for the summary class.

Good luck in your exams!



Week 13: Dec 18th

Lecture Slides: Lecture 12

Exercise: please feel free to ask all the questions from previous weeks

Lecture Recording: Link to the recorded lecture

Book Chapter: Suggested Improvements and Challenges




Week 4: 12 October

Lecture Slides: Lecture 3, same as in week 3

Exercise questions: Week 4 - Exercises, Exercise dataset

Exercise solutions : Week 4 - Solutions

Lecture Recording: Link to the recorded lecture (until 10th Nov)
                                     Link to the recorded lecture gdrive (until the end of the semester)

Book Chapter: Experimental Design: Model Fits, Power, and Complex Designs

Survey Link (Until 15th Oct): https://forms.gle/Fxh32C7vMYHyvAmEA



Week 5: 19 October

Lecture Slides: Lecture 4 (slide 57 is changed)

Exercise questions: Week 5 - Exercises, Jostmann et al., (2009), Gpower

Exercise solutions : Week 5 - Solutions

Lecture Recording: Link to recorded lecture (Until Nov 17)
                                     Link to recorded lecture Gdrive (Until the end of the semester)

Book Chapter: Experimental Design: Model Fits, Power, and Complex Designs



Week 6: 26 October

Lecture Slides: Lecture 5, Lecture 6

Exercise questions: Week 6 - Exercises

Exercise solutions : Week 6 - Solutions

Lecture Recording: Link to the recorded lecture (Until 25th Nov)
                                     Link to the recorded lecture Gdrive (Until the end of the semester)

Book chapter: The multiple testing problem



Week 7: 2 November

Lecture Slides: Lecture 6, as same as in Week 6

Exercise questions: Week 7 - Exercises

Exercise solutions : Week 7 - Solutions

Lecture Recording: Link to the recorded lecture (until 1st Dec)
                                     Link to the recorded lecture Gdrive (until the end of the semester) 

Book chapter: ANOVA




Week 8: 9 November

Lecture Slides: Lecture 7, Lecture8

Exercise questions: Week 8 - Exercises ANOVA, Exercice1_data.csv

Exercise solutions : Week 8 - Solutions

Lecture Recording: Link to the recorded lecture (until 7th Dec)
                                     Link to the recorded lecture Gdrive (until the end of the semester)

Book Chapter: Experimental Design: Model Fits, Power, and Complex Designs




Week 10: 23 November

Lecture Slides: Lecture 8 - Validity, Lecture 9

Exercise questions: Week 10 - Exercises

Exercise solutions : Week 10 - Solutions

Lecture Recording: Link to the recorded lecture (until 20th Dec)
                                     Link to the recorded lecture Gdrive (until the end of the semester)

Book Chapter: Meta-analysis




Week 11: 30 November

Understanding Replication

Lecture Slides: Lecture 10

Exercise questions: Week 11 - Exercises & Solutions

Lecture Recording: Link to the recorded lecture (until 29th Dec)
                                     Link to the recorded lecture Gdrive (until the end of the semester)

Book Chapter: Understanding Replication




Week 12: 7 December

Lecture Slides: Lecture 11

Exercise questions: Week 12 - Exercises

Exercise solutions : Week 12 - Solutions, R analysis script

Lecture Recording: Link to the recorded lecture (until 5th Jan)
                                     Link to the recorded lecture Gdrive (until the end of the semester)

Book Chapter: Magnitude of Excess Success




Week 13: 14 December

Lecture Slides: Lecture 12

Exercise: please feel free to ask all the questions from previous weeks

Lecture Recording: Link to the recorded lecture (until 12th Jan)
                                     Link to the recorded lecture Gdrive (until the end of the semester)

Book Chapter: Suggested Improvements and Challenges