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Spring 2019

DATA 71000 - Data Analysis Methods #59983
Wednesday, 6:30 - 8:30 PM, 3 Credits, Prof. Mariya Bessonov (

The goal of this course is to provide students with an introduction to basic statistical techniques for analyzing data. Students will develop an understanding of concepts underlying modern statistics and statistical reasoning that will equip them with tools to analyze variety of data types and data sources and also visualize it. We will first learn principles of descriptive statistics. Next, we will cover principles and techniques of inferential statistics, and design of experiments. Students will explore various statistical measures and techniques for analyzing data, and practice applying this knowledge to real-world data problems. Practical topics include: descriptive and inferential statistics, sampling, experimental design, statistical models, parametric and non-parametric tests, ordinary least squares regression, logistic regression, and explorative data analysis.

DHUM 73700 - Geospatial Humanities # 59981
Thursday, 6:30 - 8:30 PM, 3 Credits, Prof. Jeremy Porter (

This course aims to familiarize students with GIS and spatial analysis tools and techniques used in the visualization, management, analysis, and presentation of geo-spatial data.  The course will be a hand's on applied course in which students will learn to work with publicly available geo-spatial data in open-source software packages, including but not limited too: R, Python, QGIS, and CartoDB.  Topics covered include, Data Acquisition, Geo-Processing, Data Visualization, Cartography, Spatial Statistics, and Web-Mapping.