Policies

Meetings

We have weekly lectures Wednesday mornings from 10-10:50 AM in 100 Broad. On Mondays, you may attend one of the two lab sessions, either 1-4pm or 7-10pm, both in 328 SFL. Bring your laptop and charger. You should always attend the same lab session (either 1pm or 7pm), unless you have a conflict and let the course instructors know.


Attendance at lecture and participation in lab sessions are mandatory; 20% of your grade depends on it.


Lab sessions

In each three-hour lab session, you are expected to actively work through the tutorials with the instructors. As such, you will be writing live code in a .py file. This file must be emailed to bebi103 at caltech dot edu at the end of each lab session to get credit for attendance in the lab session. The subject line of the email should be "lastname firstname tutorial # yy/mm/dd", where the # sign is replaced by the lab session number.

Homework

Homework will be assigned roughly weekly. The homework assignments will typically have one or two short questions about the theory behind the analysis featured in the problem set, but will mainly consist of actually working up real (and in some rare cases contrived) data.


Data analysis is almost always a collaborative effort in both research and industry. Therefore, you will be assigned to groups of three (possibly with a couple groups of four depending on course enrollment). You will submit your homework as a group. The following homework policies apply.


Grading

80% of your grade is determined from homework. Everyone in your group will get the same grade on the homework.


20% of your grade is determined from participation in the lab sessions. You are expected to work together with the course instructors and fellow students as we go through the tutorials with your full attention.


Collaboration policy and Honor Code

Most importantly, much of the data we will use in this course is unpublished, generously given to us by researchers both from Caltech and from other institutions. They have given us their data in good faith that it will be used only in this class. It is therefore imperative that you do not disseminate the data sets anywhere outside of this class.


Since the homework is done in assigned groups, you obviously should collaborate heavily with the other members of your group. You are free to discuss the homework with other groups, including via Piazza, but the work you submit must be the work of your own group.


You may not consult solutions of homework problems from previous editions of this course.


You are free to consult references, literature, websites, blogs, etc., outside of the materials presented in class (the obvious exceptions being last year's homework solutions). In fact, you are encouraged to do so. If you do, you must properly cite the sources in your homework. Be warned: doing homework by Google fishing will not work! The problems are too open ended and the techniques are too varied.


Excused absenses/extensions

Under certain circumstances, missed lab or lecture sessions will be excused and extensions given on the homework. The reasons for the excuses or extensions must be compelling, such as health or family issues. They must be requested from the course instructor.


Course communications

You are free to contact the course staff at any time, but we encourage you to use the class Piazza page for questions course topics and homework. Most of our mass communication with you will be through Piazza, so be sure to set your Piazza account to give you email alerts if necessary.