In this notebook, you'll explore the iconic mtcars dataset. Why mtcars? Because it is a classic pedagogical dataset and there is A LOT written about it online. Every complicated concept we encounter, you should be able to google the name plus mtcars and find some information about it. So for example, when we study linear regression, you'll be able to google "linear regression mtcars" and find a million billion tutorials that use this dataset to teach regressions. It will give us a common vocabulary with other learners around the world.
notebook-0.ipynbis about getting to know the dataset and practicing some basic R functions (try not to use ChatGPT today)notebook-1.ipynbis about plotting distributions in one variable (as we have been doing)notebook-2.ipynbis about a new topic - comparing variables to one another
You may have to do some of your own research about mtcars. Google around for documentation. The last section asks you to do more exploratory data viz, but this time with scatter plots in two dimensions, focusing on the ways in which the variables are related to one another. We start out with a question about fuel efficiency (mpg), but we'll move on to thinking more generally about how these variables relate to one another.
This is an instance of Dhrumil's generic R + Python notebook found below: https://nbviewer.jupyter.org/github/dmil/jupyter-quickstart/blob/master/notebook.ipynb