What do I have to do for this week?

Date Finish reading/watching Submit (by 4PM by default) How to submit
October 2 Git/Github tutorial prefacing A1 A1 ( HTML ) Your github (give me the link!)
October 16 Readings listed at the top of A2 A2 ( PDF ) Your github
November 13 (No class) Proposal for the final project (click here for information) Email me
November 20 Readings listed at the top of A3 A3 ( PDF ) Your github
November 27
December 11 Your github
December 22 (Friday) Final project Email me

Materials

Functions used in class from Week 5

The template version of the in-class Rmd from Week 6 (we weren’t able to finish filling in the in-class one due to a package problem on the server, but that’s now solved)

Functions used in class from Week 5

My final version of the in-class Rmd from Week 5

Functions used in class from Week 4

The template version of the in-class Rmd from Week 4 (we didn’t modify it)

My final version of the in-class Rmd from Week 3

Functions used in class from Week 3 (only the functions that weren’t in Assignment 2 - use your own functions for the rest)

My final version of the in-class Rmd from Week 2

Lecture notes ( HTML PDF )

Readings on Zotero

Course overview

This course has two parts.

During the fall semester 2017, we’re going to learn about statistics in a hands-on way. You don’t need to have any background - we’ll start from somewhere near zero. You’ll learn some basic R, come to understand basic statistcal concepts, and learn how to put these together into simple data analysis. This is a half course (actually, 7/12). We’ll only meet every two weeks (except the 4th and 11th of December). During the intervening time, you’ll have assignments to do, which you’ll submit online before the next class. At the end of the first semester, you’ll have a project to submit.

In the spring of 2018, we’ll meet five times to work on, and discuss as a group, all the data-related issues in your mémoires which have arisen since the by-then-distant first semester, and which now must be addressed. More details on this to come.

Evaluation

  1. Five assignments: 80% total

Submitted online using Github (this will be explained in the first assignment). I will only look at changes pushed by the start time of the class where the assignment is marked as due (the class after the one where they were assigned).

  1. Project. 20% (15% project + 5% proposal) Describe a data analysis problem, give some example data, and demonstrate a dependent measure an analysis that demonstrably works to answer the question posed in the problem.

Class schedule

Schedule: Mondays, 4:00 PM - 6:00 PM in ODG 309.

In the Spring, we’ll schedule the workshop weeks towards the second part of the semester.