Seminar in Statistics: Computer Age Statistical Inference

Autumn semester 2017

General information

Professor Marloes Maathuis
Assistants Emilija Perkovic, Dominik Rothenhäusler
Lectures Mon 15-17 HG D 7.2 >>
Course catalogue data >>

Course content


We study selected chapters from the book "Computer Age Statistical Inference: Algorithms, Evidence and Data Science" by Bradley Efron and Trevor Hastie.


During this seminar, we will study roughly one chapter per week from the book "Computer Age Statistical Inference: Algorithms, Evidence and Data Science" by Bradley Efron and Trevor Hastie. You will obtain a good overview of the field of modern statistics. Moreover, you will practice your self-studying and presentation skills.


Bradley Efron and Trevor Hastie (2016). Computer Age Statistical Inference: Algorithms, Evidence and Data Science. Cambridge University Press, New York. ISBN: 9781107149892.


  • September 7th 2017:
    Assignment of topics: The first two topics will be assigned per email before the start of the semester. The remaining topics will be assigned in the first class, on Monday 25/09/2017. We will send out a doodle beforehand so that you can indicate your interests.
  • September 5th 2017:
    Welcome to the class website! The first class will take place on September 25/09/2017. We are looking forward to seeing you then.

Course materials and schedule

We will study selected chapters from the book Computer Age Statistical Inference: Algorithms, Evidence and Data Science by Bradley Efron and Trevor Hastie. The first lecture is introductory and will be given by Prof. Marloes Maathuis on September 25th. The first student presentation takes place on October 2nd.

The group of 24 students will be divided into 12 pairs. Everyone is expected to participate actively during all lectures. Moreover, each pair will have a special role during three different lectures: once as presenters, once to take the lead in asking questions, and once to give feedback.

The presentations should be roughly 2 x 25 minutes, with a 5-10 minute break in between. The assistants will meet with you twice before your presentation, to answer questions about the material and to give feedback on your planned presentation. More detailed guidelines for the presentations will be given during the first class. Please also see the FAQ for further details.

Week Topic Questions and Feedback Slides
Week 1 (25/09/2017) Introduction / Assignment of the topics.
Week 2 (02/10/2017) Group 1: Frequentist Inference, Fisherian Inference and Maximum Likelihood Estimation (Ch. 2 and Ch. 4)
  • Students: Sven Heberle and Eleni Karavouzis
  • Assistant: Dominik
  • Questions: group 3
  • Feedback: group 5
Week 3 (09/10/2017) Group 2: Bayesian Inference and Empirical Bayes (Ch. 3 and Ch. 6)
  • Students: Vladimir Fomin and Rashid Khorrami
  • Assistant: Emilija
  • Questions: group 4
  • Feedback: group 6
Week 4 (16/10/2017) Group 3: James-Stein Estimation and Ridge Regression (Ch. 7)
  • Students: Clemens Jeger and Emilien Jules
  • Assistant: Dominik
  • Questions: group 5
  • Feedback: group 7
Week 5 (23/10/2017) Group 4: Generalized Linear Models and Regression Trees (Ch. 8)
  • Students: Franco de Bardeci and Gong Zheng
  • Assistant: Emilija
  • Questions: group 6
  • Feedback: group 8
Week 6 (30/10/2017) Group 5: Survival Analysis and the EM Algorithm (Ch. 9)
  • Students: Tobias Wyss and Florian Krach
  • Assistant: Dominik
  • Questions: group 7
  • Feedback: group 9
Week 7 (06/11/2017) Group 6: The Jackknife and the Bootstrap (Ch. 10)
  • Students: Yefei Ma and Tinatin Mamageishvili
  • Assistant: Emilija
  • Questions: group 8
  • Feedback: group 10
Week 8 (13/11/2017) Group 7: Bootstrap Confidence Intervals (Ch. 11 and Ch. 20.2)
  • Students: Jinzhou Li and Stefan Hadorn
  • Assistant: Dominik
  • Questions: group 9
  • Feedback: group 11
Week 9 (20/11/2017) Group 8: Cross-Validation and Cp Estimates of Prediction Error (Ch. 12)
  • Students: Tobias Ruckstuhl and Fabian Patronic
  • Assistant: Emilija
  • Questions: group 10
  • Feedback: group 12
Week 10 (27/11/2017) Group 9: Large-Scale Hypothesis Testing and FDRs (Ch. 15)
  • Students: Weigutian Ou and Claudio Orellano
  • Assistant: Dominik
  • Questions: group 11
  • Feedback: group 1
Week 11 (04/12/2017) Group 10: Sparse Modelling and the Lasso (Ch.16)
  • Students: Aline Schillig and Johannes Abegglen
  • Assistant: Emilija
  • Questions: group 12
  • Feedback: group 2
Week 12 (11/12/2017) Group 11: Random Forests and Boosting (Ch. 17)
  • Students: Pascal Oswald and Armin Fingerle
  • Assistants: Dominik
  • Questions: group 1
  • Feedback: group 3
Week 13 (18/12/2017) Group 12: Neural Networks and Deep Learning (Ch. 18)
  • Students: Wendel Liu and Maurice Weber
  • Assistants: Emilija
  • Questions: group 2
  • Feedback: group 4


  1. I am on the waiting list, when will I know if I am able to attend the course?

    Currently, all 24 places are taken. If some students drop the course, the students from the waiting list will get a chance to attend. We will know the final list of students on the 2nd of October.

  2. When and how will the presentations be assigned?

    We will assign the first 2 presentations before the start of the semester. The remaining presentations will be assigned on the 25th of September. We will send out an anonymous doodle beforehand so that you can indicate your interests.

  3. How long should the presentation be?

    The total presentation time is 50 minutes. Each student should present roughly half the time. We advice you to split the presentation in two parts of about 25 minutes each, with a 5-10 minute break in between. Make sure to practice so that you don't go over your time!

  4. Do I have to present proofs from the text book?

    No. We encourage you to focus on getting the main ideas accross. In this respect, examples and intuition are often more useful then formal proofs.

  5. Do I have to present all examples from the text book?

    No, you can determine which examples are best for your presentation.

  6. Should I use a template for my slides?

    You can use any template you like. We recommend using one of the ETH presentation templates.

  7. How should the presentation be structured?

    The main purpose of the presentation is not to show what you have learned from reading the chapter, but to transmit this knowledge to the audience. So after studying the material, please take a step back and try to put yourself in the shoes of the audience: What would they already know? What would they find most interesting? What would be helpful examples? We highly encourage you to try to interact with the audience during your presentation.
    We will also detailed guidelines for the presentations during the first lecture. You may also find it useful to read this guideline from a previous seminar. (For this seminar we do not require that you prepare a handout.)

  8. Do I need to bring my own laptop to present my slides?

    Ideally, yes. If you do not have a laptop, or you do not have a way of connecting to an hdmi or vga connector, please let the assistants know in advance.

  9. Will my slides be published somewhere?

    Yes, all slides will be published on the course website after the presentation. Please make sure to respect copyright. In particular, if you include any images or tables not made by you in the presentation, make sure to include the source of the image/table as well.

  10. Do I need to prepare a handout?

    This is optional. If you choose to prepare a handout, please make sure to bring 26 copies. The handout will also be posted online with your presentation.

  11. What is the role of the assistants?

    The assistants give you guidance and feedback prior to your presentation. You will have a chance to meet with them twice in the week before your presentation. The first meeting will be on Monday the week before your presentation, directly following the seminar. The second meeting will be on the Friday just before your presentation. The assistants are also happy to answer any other questions that are not answered in this FAQ.

  12. What do the questions and feedback groups do during a presentation?

    The questions group studies the chapter that is being presented in advance. They follow the presentation extra closely and take the lead in asking questions, for example if some terms or ideas are not clearly explained. Of course, the rest of the class should also participate acitvely and ask questions!
    After the presentation and questions, the feedback group will give constructive comments on the strengths and weaknesses of the presentation.