- Rob Faludi - http://www.faludi.com -
Syllabus-Crafting With Data
Posted By faludi On August 14, 2009 @ 2:41 pm In | No Comments
Crafting With Data
NYU, Tisch School of the Arts
Interactive Telecommunications Program
Instructor: Rob Faludi
Contemporary interaction designers and artists often manipulate scientific, historical, commercial and social information. Literacy in design, art or engineering requires the complement of literacy in data. This class makes a powerful addition to your existing skill set of programming, visual design and electronics. Students will become conversant in the tools available for extracting insightful information from real-world samples. In this class we learn about the “lies, damn lies and statistics” that are encountered in our daily information feeds. Basic training is provided in a variety of handy methods for interpretation and manipulation of data, yet no math beyond some simple arithmetic is required for completing this course. Materials are visually oriented, and the focus is on concepts rather than on mechanics. Exercises include analyzing maps, building physical models and exploring information via accessible computer simulations. Short projects teach how to understand where data comes from, what it looks like and what it means. Students will earn how to transform data in ways that avoid distortions, reveal truths and grandly illuminate their ideas. Note: The class is carefully structured to support your other production classes. There are a variety of weekly assignments but no final project or paper, allowing you time to apply your newfound skills.
Students will develop their data literacy. They will gain a deeper understanding of how collections of information are properly created, examined, manipulated and presented. Assigned projects will explore data gathering, comprehension, exploratory analysis, parameters, probability, signal processing, prediction, confirmation and ethics.
Article Assignment: Locate an article that apparently uses data or statistics well, and one that appears to be misleading. Note your thoughts on each so you can quickly present them to your group in class the next week.
Arduino Data Gathering: Use an Arduino to gather 500 samples of interesting data in two different conditions (1000 samples total). Post your data online so it can be downloaded.
Self Portrait: Data is factual information; science finds its story. But data isn’t only about science so we can turn that on its head. Find data for your own story. Create a self-portrait, using data.
Africa Survey: Conduct a survey, as described in the assignment handout.
Discovery Seeker: Use data to seek out a discovery. Gather original data that seeks to answer a question, unravel a mystery, solve a problem, prove a point or reveal a truth. The best way to have a good idea is to have a lot of ideas, so put that into practice by presenting six different ideas to the class and enlisting their help to choose one. Gather your own pilot data, share for critique, improve your technique and gather more. Explore your data and share it for another critique, then use what you learn to gather sufficient samples for your purpose. Explore again, check for significances, patterns, correlations or trends. Finally, tell your data’s story clearly, ethically, accurately, attractively, engagingly and persuasively.
Coin Toss: An investigation of the difference between the perception and realities of random
Quincunx: Get to know the normal distribution intimately by building your own quincunx or Galton box. You may use either physical materials or create an imaginative software simulation.
Class participation & attendance 30%
Presentations and assignments 40%
Projects and documentation 30%
To Be Announced
Making the Most of It:
For best results, come to class early, participate in discussions, ask lots of questions, offer copious and constructive feedback, stretch yourself and have fun.
“We don’t receive wisdom; we must discover it for ourselves after a journey that no one can take for us or spare us.” —Marcel Proust
Article printed from Rob Faludi: http://www.faludi.com
URL to article: http://www.faludi.com/teaching/crafting-with-data/syllabus-crafting-with-data/
URLs in this post:
 http://rob.faludi.com/teaching: http://rob.faludi.com/teaching
 The Scientific Method: http://phyun5.ucr.edu/~wudka/Physics7/Notes_www/node5.html
 Feltron Annual Report: http://feltron.com/ar08_01.html
 The Function of Measurement in Modern Physical Science: http://www.compilerpress.ca/Competitiveness/Anno/Anno%20Kuhn%20Function%20of%20Measurement.htm
 Descriptive Statistics: http://davidmlane.com/hyperstat/desc_univ.html
 How to Lie with Statistics: http://www.amazon.com/How-Lie-Statistics-Darrell-Huff/dp/0393310728/
 The Canon: http://www.amazon.com/Canon-Whirligig-Beautiful-Basics-Science/dp/0547053460/
 The Lady Tasting Tea: http://www.amazon.com/Lady-Tasting-Tea-Statistics-Revolutionized/dp/0805071342/
 The Structure of Scientific Revolutions: http://www.amazon.com/Structure-Scientific-Revolutions-Thomas-Kuhn/dp/0226458083/
 How to Lie with Maps: http://www.amazon.com/How-Lie-Maps-Mark-Monmonier/dp/0226534219/
 The Ghost Map: http://www.amazon.com/Ghost-Map-Londons-Terrifying-Epidemic/dp/1594482691/
 A Mathematician Reads the Newspaper: http://www.amazon.com/Mathematician-Reads-Newspaper-Allen-Paulos/dp/038548254X/