Master of Urban Spatial Analytics
Analytic Courses - Fall 2006
Time: Friday 9 a.m.-12 p.m.
Instructor: Hillier
Description: This hands-on introduction to using geographic information system (GIS) will focus on how GIS can be applied to housing, land-use planning, redistricting, public health, historic preservation, criminology, and urban history. The class will focus almost exclusively on vector GIS data, which is appropriate for representing discrete objects such as parcels, districts, and census geography.
Time: Tuesday 5:30-8:10 p.m.
Instructor: Tomlin
Description: This course explores the nature and use of digital geographic information systems (GIS) for the analysis and synthesis of spatial patterns and processes through "cartographic modeling." Cartographic modeling is a general but well defined methodology that can be used to address a wide variety of analytical mapping applications in a clear and consistent manner. It does so by decomposing both data and data-processing tasks into elemental components that can then be recomposed with relative ease and with great flexibility.
Time: Tuesday 1:30-4:30 p.m.
Instructor: Tomlin
Description: Explore the nature and use of raster-oriented geographic information systems (GIS) for the analysis and synthesis of spatial patterns and processes.
Time: Tuesday, Thursday 12-1:30 p.m.
Instructor: Allison
Description: This course is an introduction to the practice of statistics in social and behavioral sciences. It is open to beginning graduate students and—with the permission of the instructor--advanced undergraduates. Topics covered include the description of social science data, in graphical and non-graphical form; correlation and other forms of association, including cross-tabulation; an introduction to probability theory; the logic of sampling; the logic of statistical inference and significance tests. Some data manipulation will require the use of a statistical computer "package," STATA; but the greater emphasis of the course will be on conceptualization and the ability to manipulate these new ideas both with and without access to statistical software. There is a lecture twice weekly and a mandatory "lab." (Please note: this course may be waived by students who demonstrate a sufficient statistical training background.)
Time (choose one): Wednesday 11 a.m.-12 p.m., Wednesday 3-4 p.m or Wednesday 5-6 p.m
Description: This course is an introduction to the practice of statistics in social and behavioral sciences. It is open to beginning graduate students and—with the permission of the instructor—advanced undergraduates. Topics covered include the description of social science data, in graphical and non-graphical form; correlation and other forms of association, including cross-tabulation; an introduction to probability theory; the logic of sampling; the logic of statistical inference and significance tests. Some data manipulation will require the use of a statistical computer "package," STATA; but the greater emphasis of the course will be on conceptualization and the ability to manipulate these new ideas both with and without access to statistical software. There is a lecture twice weekly and a mandatory "lab." (Please note: this course may be waived by students who demonstrate a sufficient statistical training background.)
Time: TBA (Preterm: August 2006)
Instructor: TBA
Description: This 18-hour course introduces statistical ideas as they apply to managers. It is designed for students with no prior experience with statistical analysis. Two key ideas dominate the material: summarizing and describing data, and modeling variability and randomness using probability models. The focus of the presentation is on understanding the rationale for modern statistical methods and developing critical judgment in the use of these methods. Extensive use of computer software replaces much of the standard demand for calculation and frees time for interpretation and evaluation. Topics covered in the course include: randomness and variability, graphical summarization, quality control, probability, sampling, estimation, confidence intervals, and hypothesis tests. Please note: The material covered in STAT 603 will not be covered again in STAT 621. Students taking STAT 621 will be expected to be proficient in the foundation materials covered in STAT 603.
Time: TBA
Instructor: TBA
Description: This course explores the use of the key statistical methodology known as regression analysis in solving business problems. Regression analysis permeates most of applied statistics. This course considers the application of regression in various contexts, such as the prediction of future sales and the response of the market to price changes. The use of regression diagnostics and various graphical displays supplements the basic numerical summaries and provides insight into the validity of the models. Specific important topics covered include least squares estimation, residuals and outliers, tests and confidence intervals, correlation and autocorrelation, collinearity, and randomization. The presentation relies upon computer software for most of the needed calculations, and the resulting style focuses on construction of models, interpretation of results, and critical evaluation of assumptions.
Prerequisite: In addition to basic mathematical skills (algebra and calculus), students beginning this course should be familiar with random variation and outliers, the normal probability model, confidence intervals and hypothesis tests, p-values, and univariate data displays such as histograms and normal plots. (Content of Stat 603)
Time:Wednesday 2-5:00 p.m.
Instructor: Hillier
Description: This course will introduce students to the principles behind Geographic Information Science and applications of Geographic Information Systems (GIS) in the social sciences. Examples of GIS applications in social services, public health, criminology, real estate, environmental justice, education, history, and urban studies will be used to illustrate how GIS integrates, displays, and facilitates analysis of spatial data through maps and descriptive statistics. Students will learn to create data sets, through primary and secondary data collection, map their own data, and generate and test research hypotheses. The course will consist of a weekly lecture and a weekly lab session.
Analytic Courses - Spring 2007
Time: Wednesday 12-3 p.m.
Instructor: Tomlin
Description:Study the fundamental conventions and capabilities of GIS from a broad and practical perspective. Engage in hands-on training in the use of one particular GIS and relate these skills to the more general context of theoretical concepts and current professional practice.
Time: Wednesday 5:30-8:10 p.m.
Instructor: Tomlin
Description: This course offers a broad and practical introduction to the acquisition, storage, retrieval, maintenance, use, and presentation of digital cartographic data with both image and drawing based geographic information systems (GIS) for a variety of environmental science, planning, and management applications. Its major objectives are to provide the training necessary to make productive use of at least two well known software packages, and to establish the conceptual foundation on which to build further skills and knowledge in late practice.
Time: Tuesday, Thursday 4:30-6:00 p.m.
Instructor: Smith
Description: The course is designed to introduce students to modern statistical methods for analyzing spatial data. These methods include nearest-neighbor analyses of spatial point patterns, variogram and kriging analyses of continuous spatial data, and auto regression analyses of area data. The underlying statistical theory of each method is developed and illustrated in terms of selected GIS applications. Students are also given some experience with ARCMAP, JMPIN, and MATLAB software.
Time: Tuesday, Thursday 12-1:30 p.m.
Instructor: Bielby
Description: A course in applied linear modeling. Emphasis on the theory and practice of multiple regression and analysis of variance, with extensions to path analysis and other simultaneous equation methods. Some data manipulation will require the use of a statistical computer "package," STATA; but the greater emphasis of the course will be on conceptualization and the ability to manipulate these new ideas both with and without access to statistical software. (Please note: this course may be waived by students who demonstrate a sufficient statistical training background.)
Time (choose one): Thursday 2-3 p.m., Thursday 4-5 p.m. or Thursday 5-6 p.m.
Description:A course in applied linear modeling. Emphasis on the theory and practice of multiple regression and analysis of variance, with extensions to path analysis and other simultaneous equation methods. Some data manipulation will require the use of a statistical computer "package," STATA; but the greater emphasis of the course will be on conceptualization and the ability to manipulate these new ideas both with and without access to statistical software. (Please note: this course may be waived by students who demonstrate a sufficient statistical training background.)
Time: Thursday 9-10:30 a.m.
Instructor: Hillier
Description:Geographic space is important to family and community well-being, as we know. Community Mapping introduces students to geographic information systems (GIS), computer software for making maps and analyzing spatial data. Students will learn how maps have been used in social welfare history as well as how GIS can be used for needs assessments, asset mapping, program evaluation, and program planning. The course builds on research skills developed in SW 715. For the final project, students have an opportunity to apply their GIS skills to creating maps related to their field placement. The use of such maps may lead to both program and policy change in neighborhoods and communities. Macro Practice Elective.