Week 5 - Communicating data science results effectively
Tips for effective data visualization, communication of results, and collaboration :speech_bubble:
- Watch the videos
- Complete the readings
- Complete the assignments
- Especially work on the project proposal
|Due this week|
|Lab 03||Nobel laureates||Tue, 20 Oct, 16:00 UK|
|PE 01||Peer evaluation 01 (emailed via TEAMMATES)||Wed, 21 Oct, 16:00 UK|
|OQ 04||Coding style||Sun, 25 Oct, 23:59 UK|
|Due next week|
|Project||Proposal||Tue, 27 Oct, 16:00 UK|
|HW 02||Majors + legos||Thur, 29 Oct, 16:00 UK|
If you’re having difficulty accessing your HW or Lab repo, see troubleshooting advice here.
|📖||R4DS::Chp 7 - Exploratory data analysis||Required|
|📖||IMS::Sec 2.3 - Effective data visualisation||Required|
|📖||IMS::Sec 1.3 - Sampling principles and strategies||Required|
|📖||IMS::Sec 1.4 - Experiments||Required|
|📖||Tidyverse style guide::Part 1 - Analyses (Chp 1-5)||Optional|
You can find starter code for this session on RStudio Cloud, in the project titled Code Along 05 - Baby names + coding style.
Interactive R tutorials
The following are interactive R tutorials, designed to give you more practice with R. These are optional, but they will show up in your next homework assignment, so you should gain familiarity with it. If you’re struggling with any of the topics covered this week, we strongly recommend you work through the interactive tutorials.
|Lego sales||Related to HW 02|