FAQ for current students

Note: The regulations contain all legally binding information on the MSc Statistics. Every student must have read it!

Q: What requirements do I have to meet in order to finish the MSc successfully?

A: Please check the regulations(esp. Art. 34) for the detailed rules. Keep in mind that you are responsible to stick to these rules. However, we'd like to help you by summing up the most important rules for you. As a rough outline, you need the following to finish the MSc:

• Visit one lecture in each of the five core topics (Regression, ANOVA, Time Series, Multivariate Statistics and Mathematical Statistics); get at least 20 CP in the core topics. You have to take one course in each category; each category (apart from ANOVA) has a theoretical and an applied lecture. You have to visit exactly one of them (i.e., you cannot visit both).
• Get at least 15 CP in mathematical and statistical Electives.
• Get at least 10 CP in an Applied Area (see question on applied area below).
• Get at least 2 CP in the GESS department (maximum of 4 CP are credited in GESS).
• Get at least 4 CP from a seminar (StatsLab is more applied, Seminar is more theoretical) (instead of the seminar, you can make a semester project but only if you find a supervisor and have a reason not to go to the seminar; we encourage you to do the seminar and not the semester project)
• Finish your Master Thesis (worth 30 CP).
• You must have at least 90 CP in total. If you stick to the minimal requirements in each category, you only end up with 81 CP. You have to take additional credit points in some of the above categories (apart categroy "Master Thesis", which is fixed to 30 CP) to get the full 90 CP.

Q: How do I enrol for courses? Is there a limit on the number of students?

A: You enrol via mystudies. There is almost never a limit on the number of students for a course (apart from seminars). If you figure out during the semester, that you don't want to take a lecture after all, you can just drop it. As long as you don't enrol for the final exam, it will not be mentioned in your diploma.

Q: How many credit points should I aim for each semester?

A: You need 60 credit points from courses to finish your MSc. You need one semester for the master thesis, which is worth 30 credit points (giving a total of 90 credit points). So, if you want to finish after 1.5 years, you have two semesters for the courses. Hence, you should aim for 30 credit points each semester. If you want to finish after 2 years, you can take three semesters for the courses and hence should aim for 20 credit points each semester. Most students finish after 1.5 to 2 years.

Note that 30 credit points per semester really needs your full time efforts. As a rough guide, you should expect about 2 hours solid work per week per credit point. So, if you have 20 credit points in a semester, you should expect to work about 40 hours each week. If you have 30 credit points in a semester, you should expect to work about 60 hours each week.

I suggest that you plan to do one or two very easy lectures (from GESS or Applied Area; not more than 5 CP in total) while you do your master thesis. This reduces the burden on the previous semesters a bit.

Q: Two lectures I want to attend take place at the same time. What should I do?

A: Because the stat/math electives (less so the core courses) are offered not only for the MSc Statistics, there might be a timing conflict between two or more lectures. It is very important, that you check your timetable for conflicts! Unfortunately, lecture times can not be changed. So, you have two options:

• Book both courses anyway and take exams. This is technically possible, but not at all recommended. It will be much harder for you to pass the exams that way. Only consider this option, if there is only partial overlap which makes you miss the exercise classes of one course. You might also consider this option, if there is only partial overlap and one course only lasts part of the semester ("Blockkurse").
• You look for an alternative that has no conflict. This is the recommended option.

Q: When do the exams usually take place?

The definitive details of the exams are shown in the course description of the course catalogue. As a rough guide, all exams will be during the semester break, usually rather at the end of the semester break. These exams are called "session exams" in the course catalogue. So, you should reserve several weeks during your semester break to prepare for the exams. Check for each lecture you attend in the course catalogue when the exam will take place. If in doubt, ask the lecturer.

Q: Should I choose a sepcialization?

A: You can specialize into one out of three areas and have it mentioned on your diploma. The areas available are:

• Biostatistics
• Applied Statistics
• Statistical Methodology

However, you don't need to specialize into one of the three areas. Then, no specialization will be mentioned in your diploma. There are many students who choose to specialize and many who do not want to specialize.

If you specialize, you have the advantage that your diploma is at first sight proof of your ability in that field. However, if you apply in a different field, this might be a disadvantage. For example, if you specialize in Biostatistics, this is an advantage if you apply at pharmaceutical companies. However, if you change your mind and apply at an insurance company, it might be a disadvantage. They might prefer Applied Statistics or Statistical Methodology or no specialization at all.

On the other hand, if you don't specialize, you have full flexibility but your field of expertise is not apparent at first sight. You should trade off the pros and cons for yourself. Keep in mind that the diploma supplement, which will be part of your diploma, contains all your passed lectures. So you can easily indicate your field of expertise simply by referencing the diploma supplement.

Q: What do I need to do in order to get a specialization mentioned in the diploma?

A: Get at least 6 CP of stat/math electives in the specialization area and make your master thesis in your specialization area. You can check on the webpage containing all lectures to which specialization area a stat/math elective lecture belongs. We suggest that the Applied Area and your specialization should fit together.

Q: Which courses will take place next semester?

A: The ultimate reference is the ETH course catalogue (switch to english in top right corner). Select "Statistics Master" as "Programme".

Sometimes, the University Zürich next door also offers an interesting lecture. Furthermore, some courses in the stat/math Electives can count for a specialization. For your convenience, we generate before the start of each semester a webpage containing all lectures of the core courses and stat/math Electives (which might include a lecture from the university) and indicate which course is eligible for specialization.

Q: Which courses will take place after next semester?

A: The course catalogue is only binding for the next semester. However, most lectures take place every year or every other year. So, check the course catalogue for the last couple of semesters in order to find out what is typically read in the spring and fall semester. If it was in spring, it will usually stay in spring. If it was in fall, it will usually stay in fall. On the webpage of a course in the course catalogue, you will find in the third row the field "Periodicity", which tells you whether the course takes place every or every other year.

Q: Which courses should I take?

A: If you have requirements, they should get your top priority.

In general, you should first focus on getting all your core topics done. Usually, there are two to four core topics offered each semester. They should be your first priority, because some lectures don't take place every semester. So, if you miss one, you would have to wait until you can finish your degree.

Your next priority should be the statistical and mathematical electives, the seminar and the applied area; in this area, there is much more diversity, but it is still important to have a good plan. It is very important to make up your mind and plan the applied area right at the beginning of the program.

Finally, your applied area and the GESS lecture has the least priority because there is a huge variety to choose from and thus it is hard to miss any deadlines.

A popular choice for statistical and mathematical electives is Computational Statistics (every year in spring). I can highly recommend this lecture.

Q: Can I visit lectures at the University Zurich next door?

A: Yes, you can. Starting in Spring 2011, it is very simple to visit statistics lectures at the university. Sometimes, there will be statistics lectures at the university, which we think might be particularly interesting to you. We will then announce them on the webpage containing all lectures. If you want to visit lectures at the university, you have to follow three simple steps:

• Download the template for credit transfer. Fill it out and get it signed by the study coordinator (Markus Kalisch, HG G 15.2).
• Go to http://www.uzh.ch/studies/application/mobilitaet_en.html; look in the chapter "Studying at more than one university" and click on the link "Registering for studies at more than one university, Master's level". This will bring you to an online form (unfortunately in german). As an ETH student, you don't have to pay any fees (also no "late application fee"). So, the latest deadline for application is 31. January for the spring semester and 31. July for fall semester (check here).
• When you passed your exam, get a "Leistungsnachweis" (an official document indicating that you really passed the exam) from the student office at the university. Finally, bring the signed credit transfer form and the Leistungsnachweis to the study secretary at the ETH (HG G 33.1).

NOTE: For administrative reasons, it is not possible to visit UZH lectures in your first semester (e.g. if you start fall 2012, the earliest time to visit UZH lectures is spring 2013; this is e.g. relevant, if you want to take the UZH lecture "Likelihood Inference")

The above mentioned procedure works for all university lectures that are offered in the maths/science department of the university (this includes all statistics lectures). Taking courses in other departments is also possible, but there will be a higher administrative burden. If you are interested, contact your study coordinator (Markus Kalisch, HG G 15.2).

Q: What is the GESS department?

A: The GESS is the german acronym for "Humanities, Social and Political Science" (search for this in the "Department" field of the course catalogue) and offers all kinds of courses from music theory over politics to Shakespeare. Every ETH student has to gain some credit points in this department. The goal is to make you culturally more aware and extend your horizon. The courses are usually not difficult, so it is possible to take this lecture during your master thesis.

Q: What is the Applied Area? Which courses should I take in this category?

A: In the Applied Area, you should visit lectures worth of at least 10 CP which give you insight into fields, where statistics could be applied. To make your choices easy, we compiled a webpage with examples of Applied Areas. Please feel free to create your own Applied Area.You don't have to select the name of your applied area from a predefined list. The only restriction is that it is not pure stat/math and has some possible potential for applying statistics. I encourage you to use the extensive resources of the ETH in this respect!

In mystudies, you will usually not be able to put a lecture into the category "Applied Area". In this case, write an email including the lecture name, lecture ID, number of creditpoints and semester when you visited together with your name and your student ID to the study secretary (studiensekretariat (at) math.ethz.ch). They will then do the assignment for you.

Q: What is the 'studyplan'?

A: We require each student to create a list of lectures he/she plans to attend (and when) in order to finish the degree. Within the first few weeks of your first semester, you make an appointment with the study coordinator (Markus Kalisch) and discuss the plan. If it is ok, you get it signed by the head of the MSc Statistics (Prof. Sara Van de Geer). Here is an Excel template and an example of a valid study plan.

The study plan is no official document. You can depart from the study plan any time after it was signed. We encourage that you discuss major deviations with the study coordinator (Markus Kalisch). This is intended as a service for you: You have to make up your mind at the beginning of your studies and plan carefully when to take which lectures to be efficient. The study plan should help you achieve this. By ETH law, you are responsible yourself to read the regulations and get all the credit points in all the categories right. We try to help you with this with the study plan and discussing it with you.

Q: How do I choose a topic for the Master Thesis?

A: It is up to you to find a supervisor for the master thesis. You can do a master thesis with people from outside the ETH (e.g. companies) but you always need at least one advisor who is professor in statistics at the ETH. Here are some suggestions for finding a good master thesis:

• Browse the webpages of the statistics professors at the ETH. Find out what their research topics are. Get in touch with them during lecture breaks. Approach them actively and ask whether they have a topic for you in due time. Oftentimes, professors have some ideas for Master Theses, which they can present you if you ask for it.
• After some lectures, you perhaps can formulate your own research interest. In this case, you should formulate the topic of your own Master Thesis and propose it to a professor of statistics at the ETH. Perhaps he or she is willing to advice you on this topic or on a variation of the topic.
• If you are interested in doing a thesis in connection with business or industry, or with a research station, try to make contacts as early as possible. Try to contact companies you are interested in and find out if they have problems that could be addressed in a master thesis. If you find something, make a proposal to a ETH professor of your choice and ask him, if he would supervise you together with some person from the company (it is crucial that in this scenario the company has someone to supervise you in addition to the ETH professor). Such collaborations are generally very welcome if they address a statistically relevant topic.

Q: What deadlines are there for Semester Projects or Master Theses?

A: For the MSc Thesis and the Semester Project, there are virtually no deadlines for signing up. You can start at any time during the whole year. Just make sure, that you found a supervisor. For example, if you find a supervisor today, you could start your Semester Project or Master Thesis tomorrow, if you like. However, we recommend that you start roughly at the beginning of the semester, since then there will be an instruction class on how to write your Master Thesis effectively (given by our PhD students).

For the Master Thesis, you need to fulfill administrative requirements in order to be able to start (you must have at least 16 CP in the core courses; you must have finished your additional requirements; you must have finished your BSc degree; see Art. 32.1 of the study regulations). Furthermore, you need to fill in a form, which the study secretary will give you.

For the Semester Project, there are no administrative requirements or form.

Q: Is there a library where I can get books from?

A: The ETH has a huge general library; visit the ETH library online. There is also a mathematics library with a wide selection of mathematical books. In both libraries, you can register as a user and take books home.

Q: I'm looking for a job. Where should I start looking?

A: The ETH and other organizations offer some excellent resources for finding a job. Here is a selection:

• www.jobservices.ethz.ch
• www.recruiting.ch
• www.math-jobs.com

Q: Who should I contact with further questions?

A: Please contact the study coordinator Markus Kalisch:
mail: kalisch@stat.math.ethz.ch
office: HG G 15.2
phone: +41 44 632 3435