Instructor: Nick Barton, Chris Wojtan
Teaching Assistant: Zuzana Masárová, Marta Dravecka, Jan Humplik
This course will focus on the concept of modelling, essential throughout science. We will first introduce the concept, emphasizing key issues such as distinguishing between good and bad models, how to develop one's own model, the benefits of simplicity vs. complexity, assumptions and their consequences, and why modelling should be done at all.
The course will focus on case studies from biology, physics, neuroscience, mathematics, and computer science, and will encourage students to work together to find solutions. Recitations will be used to introduce scientific or mathematical background material.
Weekly homework (40% of final grade), class project (40% of final grade), and a final exam (20% of final grade).
6 ECTS
Date  Topic  Instructor  Slides  Related reading  

6th Oct  Introduction, project organisation  NB/CW  
8th Oct  Approximation 1  CW  The art of insight in science and engineering  
13th Oct  Approximation 2  CW  Visualization slides  
15th Oct  Visualization and scaling  NB  Probability 1 slides  
20th Oct  Probability 1  NB  Probability 2 slides  Evolution book, chapter 28 Otto and Day 

22nd Oct  Probability 2  NB  Inference slides  Why most published research findings are false  
27th Oct  Inference  NB  How scientists fool themselves Blind analysis: Hide results to seek the truth 

29th Oct  Linear models  NB  Linear models slides  
3rd Nov  Linear models/Nonlinear recursions  NB  
5th Nov  Stability analysis  NB  Nonlinear recursions slides  Quantitative Universality for a Class of Nonlinear Transformations, When two and two do not make four: Nonlinear phenomena in ecology, Simple mathematical models with complicated dynamics  
10th Nov  Midterm presentations  NB/CW  
12th Nov  Midterm presentations  NB/CW  
17th Nov  Differential equations 0  CW  Taylor series  
19th Nov  Gaia 1  GN  
24th Nov  Gaia 2  GN  
26th Nov  Differential equations 1  CW  
1st Dec  Differential equations 2  CW  
3rd Dec  Dynamics 1  CW  
8th Dec  Holiday  
10th Dec  Dynamics 2  CW  
15th Dec  Wolbachia 1  NB  Wolbachia intro slides  
17th Dec  Wolbachia 2  NB  
5th Jan  Holiday  
7th Jan  Bjorn  BH  
12th Jan  Presentations 1  NB/CW  
14th Jan  Presentations 2  NB/CW  
19th Jan  Calin 1  CG  
21st Jan  Calin 2  CG  
26th Jan  Revision/recap  CW  
28th Jan  Exam  CW 
File  Due Date  Solutions  Notes 

HW1  19.10.2015  HW1 solutions  Notes on distribution of trailing digits 
HW2  26.10.2015  HW2 solutions  
HW3  2.11.2015  Recitation code, HW3 solution  
HW4  9.11.2015  HW4 solutions  
HW6  14.12.2015  Recitation code  
HW7  7.1.2016  Recitation code, HW7 solutions 
Date  Files 

15th Oct  Problems,data1,data2 
24th Nov  Karate_table, R solutions to recitation problems 
21st Jan  Recitation on hysteresis Mathematica gadget 
The class project consists of an interdisciplinary project on a topic of your choice related to modeling. A onepage abstract describing the goals of your project, the data, the main questions and the approaches you plan to take, is due on Monday, October 19. Midterm presentations are on November 10 and 12. Final presentations are on January 12 and 14. A final writeup of the project of maximally 10 pages will also be due at the end of semester.
Books available in the library course reserve:
 Modelling for field biologists and other interesting people (Hanna Kokko)
 A biologist's guide to mathematical modeling in ecology and evolution (Sarah Otto & Troy Day)
 Models in ecology (John Maynard Smith)
 The analysis of biological data (Michael Whitlock & Dolph Schluter)
 The art of insight in science and engineering (Sanjoy Mahajan)
 Sustainable energy  without the hot air (David Mackay) and here is the (pdf)