Browsing by Subject "Data Expeditions"
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Item Open Access 2014 Data Expeditions Call for Proposals(2015-11-30) Reiter, Jerome P; Calderbank, RobertItem Open Access 2015 Call for Proposals(2015) Bendich, Paul L; Calderbank, Robert; Reiter, Jerome PItem Open Access Ballistic jumps of trap-jaw ants and computational methods for image analysis(2014) Rosario, MichaelItem Open Access Exploring lemur olfactory communication(2015-11-30) Smyth, Kendra; Greene, LydiaIn Fall 2015, we (Kendra Smyth & Lydia Greene) led a Data Expeditions (DE) workshop in Advanced Research in Evolutionary Anthropology, a senior-level class on the research process. The goal of the workshop was to get students familiar with the R language and introduce them to a range of statistical techniques that might be useful for analyzing their own senior thesis data. In the workshop, we used a lemur scent-marking dataset compiled by Greene during her undergraduate honors thesis at Duke. By using these data, we aimed to make statistics seem both accessible and relatable to these students. Although teaching students the specific commands in R is undeniably valuable, the true reward from the Data Expeditions came from seeing students understand key concepts in statistics and from giving them the tools to begin the process of analyzing their own data.Item Open Access Major League Baseball and National Basketball Association regular season data by team(2014) Futoma, Joseph; McAlinn, KenichiroWith the rise of sports statistics, especially sabermetrics in baseball, statistics have proven crucial not only for managing teams and assessing player value, but also for forecasting team and individual performance. In this data expedition, we provided undergraduates with detailed information about each team from every NBA and MLB game during the 2010-2011 and 2013 seasons, respectively. For baseball, for each of the 2430 games we have 23 batting stats (e.g. hits, runs batted in, homeruns) and 23 pitching stats (e.g. strikeouts, runs allowed). For basketball, we have 20 stats (e.g. field goals, free throws, rebounds), for each of the 1230 games.Item Open Access Math 412: Music + Topology(2014) Tralie, ChristopherIn this mini assignment you will explore an application of "sliding windows and persistence" on time series data (see Jose Perea's paper for more theory). Specifically, you will look at how to transform musical audio data into a high dimension point cloud/curve which can be probed with TDA methods. You will make use of a visualization program called LoopDitty to gain some intuition about what points in various persistence diagrams might mean. Please follow the directions below and submit an electronic writeup to chris.tralie@gmail.com with the answers to all of the questions and any observations you have. Enjoy!Item Open Access North Carolina Traffic Stops(2014) OwensOas, DerekItem Open Access Signal, noise, and bias in yeast MNase-seq data(2014) MacAlpine, David MichaelThis is an optional challenge for students interested in applying what we have learned in class to a real computational genomics research problem; practicing the skills of using Python or R (or any other tool you wish) to visualize, analyze, model, and interpret real genomic data; and exploring the science linking chromatin structure and transcriptional regulation. Since this problem represents an open challenge for the genomics community, you are free to choose the approaches you use to analyze the data, as well as the questions you explore.