I399 : Research Methods in Informatics and Computing

Fall 2014
Ballantine Hall, Room 340
Tuesdays and Thursdays, 4:00–5:15 pm
Professor Simon DeDeo
Associate Instructor (AI) Alexander Barron

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image: Sydney Padua, The Thrilling Adventures of Lovelace & Babbage

Syllabus, Hours & Handouts

The official course syllabus is at http://santafe.edu/~simon/end_of_semester_syllabus.pdf [latest version: 4 November 2014] Mr. Barron's office hours are Tuesdays 9—11 am; after class; and by appointment; Informatics East, Fourth Floor. Prof DeDeo's office hours are Fridays, 5—7 pm, Informatics East, Room 302.

An attempt at exhausting a place in Bloomington, Indiana [first homework assignment; grading rubric]
Probability Worksheet, Solution to Probability Worksheet & Second Solution to Probability Worksheet [lecture four]
Estimating Probabilities from Data [worksheet, lecture five, due Tuesday, 16 September 2014]
Patterns and Markov Chains [worksheet, lecture seven, due Thursday, 25 September 2014]
Cheat Sheet: Pearson Correlation [quick review, lecture thirteen]
What Makes a Group Succeed?

Course Description

With the goal of preparing students to undertake original research, this course introduces basic principles and tools of quantitative research in Informatics & Computing. Particular focus on topics newly accessible to “big data” approaches; emphasis on developing research projects and building collaboration skills, including mid-semester hackathon.

Extended Description

We’ll learn by doing, and study everything from the single thinking individual up to the mass minds of contemporary networked society and down into the origins of humankind.

We’ll study how people argue on Wikipedia and troll on reddit; we’ll look for patterns in financial markets, medical care, and text message conversations. We’ll delve into the early history of computing, from Bulletin Board Systems to Doug Engelbart and the Mother of All Demos; and we’ll launch ourselves into the deep past to find the origins of our manipulative, aggressive, communicative and, finally, highly cooperative behavior.

At the same time, we’ll teach you the tools and methods you need to contribute to research. You’ll learn how to work with uncertainty and probabilities; how to detect patterns in data (and reject false ones); you’ll learn how to scrape data and predict the future; you’ll work on riots and revolutions, Bibles and court trials, and you’ll do so, often, as part of a team, to develop your skills as a leader and collaborator.


Occasional hand-outs.
One joint mid-term hackathon.
One final paper (including a draft, due separately)

The class workload is “heavy in the middle”. On-schedule progress will mean a higher workload around the middle of term, with significantly reduced work compared to a normal class at semester end.

Resources for Personal Development

Intellectual health warning: work on personal development, leadership, and life-skills currently falls well short of the rigor and proof expected in the natural sciences (you are welcome to change this). These links are provided without warranty and solely in the hopes that you will find them useful sources of views you many not have considered in the past. None of these texts are required; no endorsement is implied; placebo effects abound.

Getting Things Done. A classic text on improving personal productivity. Popular among geeks.
Articles on exercise from the New York Times: [1] [2] [3] [4] [5].
Emotionally Intelligent Leadership. A selection of articles from the Harvard Business Review.
Lois Frankel’s career guide for women (with plenty of advice useful to men).
The War of Art. Occasionally baffling book on procrastination and achievement.
Your Brain at Work. Strategies for concentration, focus, and thinking.
Difficult Conversations. Classic text on conflict resolution.
How to Pick a Graduate Advisor. Good advice for both student and mentor.

Focus at Will. Web-based program for concentration.
RescueTime. Self-monitoring software for your computer. Feedback on actual usage (LaTeX vs. reddit, e.g.)