β Week 06 - Checklist
DS202 - Data Science for Social Scientists
Here is a suggestion of how to program your week in relation to this course:
Revisit the code in π» Week 04 - Lab Roadmap & βοΈ Week 04 - Lab Solutions to reinforce your understanding of logistic regression and that of training/test split.
- In there, you will also find code to run an alternative classifier: Naive Bayes
Read the text on the π¨βπ« Week 04 - Lecture page to understand more about different training/test splits and also of k-fold cross validation.
The RMarkdown used in this lecture/workshop can be found on Moodle, under π₯W04 Lecture Files
Bookmark the page with π¨βπ« Week 05 - Lecture slides or π₯ download the PDFs
- In there, you will find code to run alternative algorithms: Decision Tree and Support Vector Machine (SVM)
Try to solve the βοΈ Summmative Problem Set (01) | W05-W07 by yourself.
Read the useful links about tidyverse (below)
Questions? Attend one of the drop-in sessions (below) or ask questions on #week06 channel on Slack
| Day | Time | Classroom | Teacher |
|---|---|---|---|
| Tue 1 Nov 2022 | 10 a.m. - 12 p.m. | FAW 3.02 | Jon (Focus on R programming) |
| Wed 2 Nov 2022 | 10 a.m. - 12 p.m. | FAW 3.02 | Mustafa |
| Fri 4 Nov 2022 | 10 a.m. - 12 p.m. | FAW 1.02 | Yijun |
Useful Links about tidyverse
tidyverse is a set of R packages that have several functions and facilities for working with data. I find tidyverse more intuitive than base R, and thereβs an entire book available for free online (R for Data Science) that contains a lot of helpful tutorials about tidyverse. Let me point to a few specific chapters:
You might need or want to transform data when working on your problem sets. Check out Chapter 5 of R for Data Science online book.
Data visualization is another helpful skill. You can learn a bit more about ggplot, the tidyverse way of making plots, in Chapter 3 of R for Data Science online book.
What should you be looking for when working with data? Check Chapter 7 to learn the basics of exploratory data analysis.
Do you get confused about R Markdown, the idea of βknittingβ a file? Then read Chapter 27.
(More advanced) Do you want to learn how to reshape data or deal with more complex data manipulation? Then have a look at Chapter 12 - Tidy data and Chapter 13 - Iteration.
Are you already familiar with tidyverse, but you constantly need to Google how to do things? Save these cheatsheets to your computer.