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Some class resources are on Slack
Using class material: Each week I'll be putting up links to video tutorials. You should review those BEFORE class. We'll use class time for labs, questions and to put that new knowledge to use.
How do lecture notes relate to videos? Notes have more detail including both more basic and more advanced material. Why? Because skimming text is much easier than skimming video so I've included more in the notes. You should take time to review the sections of the lecture notes that correspond with each video.
As you work in data, you'll hear the phrase, "the map is not the territory" along with citations to the story by Jorge Luis Borges, "On Rigor in Science". This course is not set up in an easy linear way because that's not how knowledge works -- we may lure in newbies with that fiction but this is grad school. You have a choice about how deep you want to go.
Class Lecture Notes up to p 50 should be review and of course this is a draft, might change as we go along particularly parts after p 150 or so
In class Sept 5 we'll do Lab 1
Please review these videos before that class,
L 2.1 on probability (part a),
L 2.2 part b and
L 2.3 discrete random variables.
Homework 1 due Sept 5 (well, by midnight somewhere on the globe so I'll accept uploads on Slack until 8am in NYC the next day)
Video 1.2 More R Basics with notes to go along
Video 1.1 on basics for R and Notes to go with Video 1.1 make sure to download Household Pulse data
Preliminaries: refresh your basic stats knowledge for Diagnostic Test early, start to learn R.
Download and install both R and R Studio.
We'll start using this data, a combination of Household Pulse Data from 4 years
Syllabus includes more references for learning R
Grading Policy
A Refresher on Basic Skills. Most of it should be too basic but it
needs to be communicated.
I've got several datasets in R format for you
The zip file includes the data as well as some details about how I created it. To begin you will likely only need the RData file.
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