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 |

**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)

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.

- 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).

- 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.

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

**Week 1 (September 18)**: Statistical reasoning**Week 2 (October 2)**: Tests, descriptive statistics**Week 3 (October 16)**: Statistical power**Week 4 (November 6)**: R fundamentals, bootstrap, estimation, confidence intervals**November 13**: Project proposal deadline (no class that day)**Week 5 (November 20)**: More on the bootstrap, linear regression**Week 6 (November 27)**: Contrast coding and multiple regression**Week 7 (December 11)**: Using predictions to evaluate model assumptions**December 15 (Friday)**: Project deadline

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