β Week 03 - Checklist
DS202 - Data Science for Social Scientists
Follow the suggested list of actions below to get the most out of this course:
Your Checklist:
π Read (James et al. 2021, chap. 3) to reinforce your theoretical knowledge of Linear Regression. The textbook is available online for free.
π§βπ» If you already know linear regression from previous courses you have taken, why not take this knowledge to next level?
- Try to find a dataset online that contains a numerical variable you could predict by fitting a linear regression to it. I will be curious to see what you find. Share your findings on the
#week03
channel in our Slack.
- Try to find a dataset online that contains a numerical variable you could predict by fitting a linear regression to it. I will be curious to see what you find. Share your findings on the
π₯οΈ Before you come to the class, skim the W03 lab roadmap page to have an idea of what we are going to do.
This week, instead of just typing things in the terminal, we will use R Markdown. You can read about it here. This is also how you will be submitting solutions to formative and summative assignments in the future.
I will post solutions to the practical exercises at the end of the week.
π» Assess yourself: did you understand all the exercises in the lab?
- If you are new to linear regression and you are enrolled in the Monday sessions, it is likely that you will struggle a bit in the lab. During the week, reserve some time to read about Linear Regression and then practice the exercises again.
π Struggling with something? Donβt know what a particular
R
command do? Share your questions on the#week03
channel in our Slack.- I will also be posting follow up questions on Slack during the week.
π Keep in mind that: after the lecture on Friday, 14 October 2022, we will post the first formative assignment on Moodle.
You will have until Thursday of the following week (20 October 2022) to submit your solutions.
This assignment is not marked, it doesnβt count towards your final grade, but you will receive feedback if you submit.
The assignment will have a similar format as the questions we explore in the lab.
π¨βπ« Attend the lecture. It will help you remember concepts more easily when revising later.