Student Seminar in Statistics:
The Art of Statistics

Autumn semester 2019

General information

Lecturer Marloes Maathuis
Assistants Domagoj Ćevid, Yulia Kulagina
Lectures Mon 15.00-17.00 HG D 7.2
Course catalogue data VVZ

Course content

Objective

We will study roughly one chapter per week from the book "The Art of Statistics: Learning from Data" by David Spiegelhalter. The focus of the book is not so much on technical aspects, but more on concepts, philosophical aspects, statistical thinking and communication. This will also be the focus of the class, but we may occasionally look up additional information from references that are given in the book. Besides improving your statistical thinking, you will practice your self-studying, collaboration and presentation skills.

Literature

David Spiegelhalter (2019). The Art of Statistics: Learning from Data. UK: Pelican. ISBN: 978-0-241-39863-0

Prerequisites

Besides an introductory course in Probability and Statistics, we require one subsequent Statistics course. We also expect some experience with the statistical software R. Topics will be assigned during the first meeting.

Announcements



    12.09.2019
    Welcome to the website of the course "Student Seminar in Statistics: The Art of Statistics"!
    The first class will take place on Monday, 23.09.2019.
    This will be an introductory lecture by Prof. Marloes Maathuis. Please watch the following talk by Prof. Spiegelhalter in advance.
    We are looking forward to seeing you!

    Assignment of topics: The first two topics will be assigned per email before the start of the semester. The remaining topics will be assigned during the first class, on Monday 23.09.2019. We will send out an anonymous Doodle poll beforehand, so that you can indicate your interests. The first student presentation will take place on September 30th.

    Please, let us know ASAP in case you decide not to take part in the seminar.

Course material and schedule

We will study the following book: David Spiegelhalter (2019). The Art of Statistics: Learning from Data. UK: Pelican. ISBN: 978-0-241-39863-0. Please also see the errata, code and additions on https://dspiegel29.github.io/ArtofStatistics/ .

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. One of 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 (23.09.2019) Introductory Lecture by Prof. Marloes Maathuis
Getting Things in Proportion: Categorical Data and Percentages (Ch. 1)

Please watch this talk by Prof. Spiegelhalter in advance.
Week 2 (30.09.2019) Group 1: Summarizing and Communicating Numbers. Lots of Numbers (Ch. 2)

  • Students: Casimir Fürer, Beat Jäckle
  • Assistant: Yulia
  • Questions: Group 3
  • Feedback: Group 5
Week 3 (07.10.2019) Group 2: Why Are We Looking at Data Anyway? Populations and Measurement (Ch. 3)

  • Students: Patrick Schöngrundner, Luca Pedrazzini
  • Assistant: Yulia
  • Questions: Group 4
  • Feedback: Group 6
Week 4 (14.10.2019) Group 3: What Causes What? (Ch. 4)

  • Students: Daniela Nguyen, Janosch Ott
  • Assistant: Yulia
  • Questions: Group 5
  • Feedback: Group 7
Week 5 (21.10.2019) Group 4: Modelling Relationships Using Regression (Ch. 5)

  • Students: Kristin Blesch, Johannes Bernstorff
  • Assistant: Domagoj
  • Questions: Group 6
  • Feedback: Group 8
  • Slides
  • R code
  • Week 6 (28.10.2019) Group 5: Algorithms, Analytics and Prediction (Ch. 6)

    • Students: Tim Gyger, Maic Rakitta
    • Assistant: Domagoj
    • Questions: Group 7
    • Feedback: Group 9
    Week 7 (04.11.2019) Group 6: How Sure Can We Be About What Is Going On? Estimates and Intervals (Ch. 7)

    • Students: Tanja Finger, Kevin Selänne
    • Assistant: Domagoj
    • Questions: Group 8
    • Feedback: Group 10
  • Slides
  • R code
  • Week 8 (11.11.2019) Group 7: Probability - the Language of Uncertainty and Variability (Ch. 8)

    • Students: Carlo Casati, Danish Kashaev
    • Assistant: Domagoj
    • Questions: Group 9
    • Feedback: Group 11
    Week 9 (18.11.2019) Group 8: Putting Probability and Statistics Together (Ch. 9)

    • Students: Valdrin Sherifi, Gian Wiher
    • Assistant: Yulia
    • Questions: Group 10
    • Feedback: Group 12
    Week 10 (25.11.2019) Group 9: Answering Questions and Claiming Discoveries (Ch. 10)

    • Students: Pierfrancesco Beneventano, Nicola Ruckstuhl
    • Assistant: Yulia
    • Questions: Group 11
    • Feedback: Group 1
    Week 11 (02.12.2019) Group 10: Learning from Experience the Bayesian Way (Ch. 11)

    • Students: Mian Zhong, Ruicong Yao
    • Assistant: Yulia
    • Questions: Group 12
    • Feedback: Group 2
    Week 12 (09.12.2019) Group 11: How Things Go Wrong (Ch. 12)

    • Students: Yinghao Dai, Samuel Koovely
    • Assistant: Domagoj
    • Questions: Group 1
    • Feedback: Group 3
    Week 13 (16.12.2019) Group 12: How We Can Do Statistics + Conclusion (Ch. 13 + Ch. 14)

    • Students: Yannick Busch, Fu-Hsuan Ho
    • Assistant: Domagoj
    • Questions: Group 2
    • Feedback: Group 4

    FAQ

    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 September 30th.

    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 23rd of September. We will send out an anonymous Doodle poll 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 of the time. We advise you to split the presentation in two parts of about 25 minutes each, with a 5-10 minute break in between. Please make sure to practice so that you don't go over your time! We highly encourage interaction and discussion with the audience, both during and after your talk. If this happens during your talk, this will not be counted as presentation time.

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

      No, you should select which examples are best for your presentation.

    5. Should I look at additional material beyond my assigned book chapter?

      The book is a bit special, in the sense that it is written for a general audience and for statisticians. As a result, it is very non-technical. This is not a problem, since the idea of the seminar is to focus mostly on conceptual issues. If you want to go into more detail, however, you can look at the references that are given for each chapter. You may also look for additional relevant material yourself or ask the assistant in charge for your group for pointers.

    6. Should I use a certain 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 to transmit knowledge to the audience. So, after reading the material, please take a step back and try to put yourself in the shoes of the audience: What do they already know? What would they find most interesting? What would be helpful examples? We will also provide further guidelines for the presentations during the first lecture.

    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 the projector, 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 created by yourself 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 assistant in charge for your group gives you guidance and feedback prior to your presentation. You will have a chance to meet with the assistant twice before your presentation. The first meeting will be on Thursday, 1.5 weeks before your presentation (it will be Thursday by default but it is possible to reschedule the meeting on mutual agreement). The second meeting will typically take place on Thursday, 0.5 week before your presentation (again, rescheduling rule applies).

    12. How should I prepare for the meetings with the assistants?

      For the first meeting: You should read all material in advance, make a list of questions you have, and make a rough plan of what you would like to present (main concepts, main examples, questions you could pose to the audience to create some interaction, R-example that you could integrate, etc). For the second meeting: Your presentation should be fully prepared and should be sent to the assistants the day before. During the meeting, you will get feedback on your presentation, and you can clarify any remaining issues.

    13. What do the questions and feedback groups do during the 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 actively!). After the presentation and questions, the feedback group will give constructive comments on the strengths and weaknesses of the presentation.

    14. Do I have to attend all lectures?

      Yes, attendance at all lectures is compulsory. You can miss one lecture without giving a reason. If you have to miss any further lecture, you must contact us immediately and have a good reason.