Homework 10: Course feedback (20 pts)

This homework is to be done individually, not in groups. Your responses are not to be put in your GitHub account so you can speak candidly without the influence of your teammates. You do not need to use a Jupyter notebook to do the problem. Instead, you should submit your responses as text in an email. Do not submit a MS Word document or a Jupyter notebook. Please email your responses to all of the following email addresses.

bois at caltech dot edu
dgoertsen at caltech dot edu
kaylajac at caltech dot edu
graceliu at caltech dot edu
zmartine at caltech dot edu
oguienko at caltech dot edu

A total of 20 points will be awarded for thoughtful responses for this homework. I am not expecting a paragraph for each question, but if you have detailed comments on something you have a strong or insightful opinion about, I would like to hear them.

Thank you in advance for your responses. They really do help shape what we do in future versions of the course.

10.1: Topical coverage

a) Are there topics you would like covered that were not?

b) Were there topics you think we spent too much time on?

c) Which topics did you find most interesting?

d) Which did you find most pertinent?

e) Where there any common misconceptions that persisted throughout the course for you? What topics (if any) did you find particularly hard to understand and apply?

10.2: Data sets and exercises

a) What was your favorite homework problem or data set? Which problem would you remove? Why?

b) Did you like that we kept revisiting data sets throughout the term?

10.3: Course structure

a) Where did the majority of your learning take place? (Example answers include: Reading the lessons, doing the lesson exercises, completing the homeworks, interacting with TAs during the Monday sessions, interacting with TAs during office hours, during JB’s lectures, during JB’s office hours, talking with teammates, etc.)

b) How would the class have been different for you if the work weren’t done in teams?

c) Do you have any suggestions for improvement of the Monday sessions?

d) Did you attend any recitation sessions? Did you find them useful? Do you have general suggestions for that?

e) Did you find the homework help sessions useful? Do you have general suggestions for that?

f) Do you have any suggestions for improving the course website and/or dissemination of material?

g) What are your opinions on Ed as a way to discuss course material and get help?

h) We are toying with some structural changes to the group work. What are your opinions on have some homework problems be done individually? In other words, do you think it would benefit you to have some things necessarily done on your own (aside from lesson exercises)?

10.4: Your future

a) What will you be able to do with your data that you weren’t able to before?

b) Has this class changed the way you read scientific papers? Has it changed your opinion on any papers you’ve read previously?

c) Which of the following principles do you think you will apply in your work going forward?

  1. Tidy data

  2. ECDFs

  3. Other visualization techniques we learned (please specify)

  4. Nonparametric bootstrapping

  5. Generative modeling and MLE

  6. Other principles from class or recitations?

d) Which of the following software tools do you think you will use in your work going forward?

  1. Jupyter notebooks

  2. Google Colab

  3. Git/GitHub

  4. Python-based tools in general (NumPy, SciPy, etc.)

  5. Pandas

  6. Bokeh

  7. Distribution explorer

  8. iqplot

  9. The bebi103 package (utilities we used in the course)

  10. Griffin Chure’s workflow

  11. Griffin Chure’s website template

e) Do you expect to coordinate with CaltechDATA (as discussed in Kristin Briney’s guest lecture)?

f) Will you share what you have learned with your labmates/classmates?

g) Will you share what you have learned with your PI?

10.5: Your programming background

How comfortable were you with using Python at the start of the course? Did you feel your programming skills were sufficient for the course?

10.6: Your mathematical background

What was your background in mathematics before the course? Did you feel that your mathematical background coming in to the course was sufficient to understand the course content and complete the assignments?

10.7: Future interests

a) Are you interested in taking part (b) of the course, which covers primarily Bayesian modeling?

b) We are thinking about various options for part (c), which are more special topics in data analysis. Bearing in mind that we already have a course in Bioinformatics (Bi/BE/CS 183) and one in machine learning (BE/Bi 205) are there are suggestions you have for a third term of the course?

10.8: Miscellany

Please include any comments you have that I have not asked about.