Day 21¶
Announcements¶
- Presentations will be 5 minutes per group on Thursday, November 12 (i.e., 1 week from today)
- Draft reports (~6 pages) due on Thursday, November 12 at 21:00
- Quiz on Monday, November 9 will cover hw2 material, scope, plotting, basic linear modeling as covered in Matthew’s lectures, basic Git workflow, and possibly some general questions about hypothesis testing.
- BIC tour on Monday, November 23 (during lab time)
Links¶
Technical writing
- Technical writing slides
- Appendix to “Stat Labs” by Deb Nolan and Terry Speed
- Halmos’ “How to write mathematics”
- Knuth et al. “Mathematical Writing”
Tentative final project rubric
Reports and presentations¶
“Seek simplicity, and distrust it.” — Alfred North Whitehead
- Briefly describe data (~30s)
- Paper
- dsnum from openfmri.org
- What kind of data is it?
- Briefly describe what you’ve done so far (~30s)
- data fetching/preprocessing
- initial analysis
- plots? figures?
- What is your plan? (~3m)
- What analysis will you perform?
- How does it relate to the original data analysis?
- Will you use all the data? Why or why not?
- What model/preprocessing steps will you simplify?
- What are the problems you face?
- Try to be explicit about your issues?
- Suggest potential solutions and/or approaches.
- What do you need to research more? Have you found sources?
- Will you try to make “inferences” from the data?
- How will you deal with multiple comparisons?
- How will you attempt to validate your model?
- Process (~1m)
- What was the hardest part of the process so far?
- Git workflow, Python, fMRI data, all of the above
- Having an ill-defined assignment?
- How successful have you been at overcoming these obstacles?
- What issues have you faced working as a team? How have you been addressing them?
- What parts of the class have been the most useful?
- What parts have been the least helpful or most confusing?
- What do you need to do to successfully complete the project?
- How difficult are you finding it to make your work reproducible? Do you feel confident that you are in a position to make your projects reproducible?
- What would be most helpful for your team in the remaining weeks? Additional lectures? Structured or unstructured group work?
- What potential topics would be most useful for us to cover?
- Overview of brain / neuroanatomy?
- More linear regression (ANOVA)? PCA? The mathematics or the implementation?
- Machine learning (classification, prediction, cross-validation)?
- Permutation tests (and maybe bootstrap)?
- Software tools (Git, Make, Python, statmodels, etc.)
- Technical writing and scientific visualization?
- Advanced topics (regularized regression, selective inference)?
- What was the hardest part of the process so far?
Remember¶
- If you have questions about your projects, there should be a pull request with code or text and use @jarrodmillman, @matthew-brett, @rossbar, andor @jbpoline
- Most of your code should be written as a collection of functions with tests, then use scripts calling these functions to perform your analysis