Lsci 202a: Computational Skills for Language Science Research

1 Course Information

Lecture times	MWF 1-1:50pm
Lecture Location	https://us02web.zoom.us/j/8297737939
Syllabus	http://socsci.uci.edu/~rfutrell/teaching/lsci202a-f2020
Canvas site	https://canvas.eee.uci.edu/courses/31403

2 Instructor Information

Instructor	Richard Futrell (rfutrell@uci.edu)
Instructor's office	SSPB 2215
Instructor's office hours	T 4pm

3 Course Description

This course teaches basic computer and computational skills for use in a career as a researcher in the field of Language Science. We will cover the use of command line tools, management of data and code including version control using Git, basic data analysis and visualization in R, the mechanics of running computationally complex processes on your own or remote machines, and web programming including creating and publishing an academic website.

4 Course Format

Class time will be spent on demonstrations and in-class group exercises.

Students are required to connect to class using laptops or other PCs (not tablets or phones) in order to work together on pair-programming exercises.

Students are encouraged to collaborate on homework.

Readings are optional but strongly recommended. They are short and you will find them immediately useful.

There are no exams or tests.

5 Intended audience

This course is intended for graduate students in UCI's PhD program in Language Science.

6 Schedule (subject to modification)

Day	Topic	Deadlines	Readings
10/2	Introduction
10/5	R: Visualization		R4DS Chapters 1-3
10/7	R: Visualization		R4DS Chapters 1-3
10/9	R: Visualization		R4DS Chapters 1-3
10/12	R: Workflow		R4DS Chapters 7-15
10/14	R: Relational Data		R4DS Chapters 7-15
10/16	R: Tidy Data		R4DS Chapters 7-15
10/19	R: Exercise Time
10/21	R: Exploratory Data Analysis	Exercise 1 Due	R4DS Chapters 7-15
10/23	R: Linear Models		R4DS Chapters 22-25
10/26	R: Linear Models		R4DS Chapters 22-25
10/28	R: Linear Models		R4DS Chapters 22-25
10/30	R: Linear Models
11/2	R: Linear Models
11/4	Command Line		Unix for Poets
11/6	Command Line		Regular Expression Cheatsheet
11/9	Command Line		Git guide
11/11	Veterans day (no class)
11/13	Exercise Time
11/16	Python
11/18	Python
11/20	Python	Exercise 2 Due
11/23	Python
11/25	No class (Thanksgiving break)
11/27	No class (Thanksgiving break)
11/30	Web Programming
12/2	Web Programming
12/7	Web Programming
12/9	Web Programming
12/11	Exercise Time	Exercise 3 Due

7 Requirements & Grading

Grades are based upon successful completion of exercises.

Grade breakdown

Work Grade percentage

Exercises 100%
Exercises

Exercises are assignments to write a script, perform some data analysis or visualization, to create an online experiment, or make and publish an academic website. They will be completed partially in-class in groups.
Mapping of class score to letter grade

I guarantee minimum grades based on these thresholds:

Threshold Guaranteed minimum grade

>= 90% A

>= 80% B

>= 70% C

>= 60% D

< 60% F

So for example a score of 90.0001% guarantees you an A-. It is unlikely that I will grade the course on a curve, but if I do, you could end up with a higher grade due to the curve.

Work	Grade percentage
Exercises	100%

Threshold	Guaranteed minimum grade
>= 90%	A
>= 80%	B
>= 70%	C
>= 60%	D
< 60%	F

8 Academic Integrity

We will be adhering fully to the standards and practices set out in UCI's policy on academic integrity. Any attempts of academic misconduct or plagiarism will be met with consequences as per the university regulations.

9 Disability

Any student requesting academic accommodations based on a disability is required to apply with Disability Service Center at UCI. For more information, please visit http://disability.uci.edu/.