This clinical course provides an opportunity for students to develop beginning skills in gathering patient data and providing safe basic nursing care.

This course is aimed at students who have a foundation in basic GIS techniques and applications and are interested in expanding their knowledge into their area of spatial decision making and visualization of the decision maps. We will start with the linkage between GIScience, spatial analysis, and decision support. We will then discuss different decision-making techniques and highlight the important distinction between conventional MCDA methods and spatially explicitly multicriteria approaches. An overview of handling spatial uncertainty as well as sensitivity analysis will be discussed.

This graduate-level course is aimed at students who have a foundation in basic GIS techniques and applications and are interested in expanding their knowledge into their area of spatial decision making and visualization of the decision maps. We will start with the linkage between GIScience, spatial analysis, and decision support. We will then discuss different decision-making techniques and highlight the important distinction between conventional MCDA methods and spatially explicitly multicriteria approaches.

Students will understand and implement principles of good design in cartography along with understanding the human vision and how it influences perception and cognition. The course will also cover the scope of contemporary thematic cartography and web mapping. Students will gain hands-on experience in designing and improving web-based maps.
In this course, students will:
- Learn the fundamentals of cartography and map design
- Become familiar with using open source tools to improve the visual quality of web-based and other maps

Studentswill understand and implement principles of good design in cartography along with understanding the human vision and how it influences perception and cognition. The course will also cover the scope of contemporary thematic cartography and web mapping. Students will gain hands-on experience in designing and improving web-based maps.
In this course, students will:
- Learn the fundamentals of cartography and map design
- Become familiar with using open source tools to improve the visual quality of web-based and other maps

First semester of a two-semester sequence. Emphasis given to probability theory necessary for application to and understanding of statistical inference. Probability models, sample spaces, conditional probability, independence. Random variables, expectation, variance, and various discrete and continuous probability distributions. Sampling distributions, the Central Limit Theorem and normal approximations. Multivariate calculus introduced as needed. Prerequisites: MATH 132, or 136. (Gen.Ed. R2)

Planning, statistical analysis and interpretation of experiments. Designs considered include factorial designs, randomized blocks, latin squares, incomplete balanced blocks, nested and crossover designs, mixed models. Has a strong applied component involving the use of a statistical package for data analysis. Prerequisite: previous coursework in statistics.

Point and interval estimation, hypothesis testing, large sample results in estimation and testing; decision theory; Bayesian methods; analysis of discrete data. Also, topics from nonparametric methods, sequential methods, regression, analysis of variance. Prerequisite: Statistc 607 or equivalent.

A makerspace is a physical location where people gather to share resources and knowledge, work on projects, network, and build. The `Maker Culture? emphasizes learning through doing-it-yourself, or doing-it-together, in a social environment and utilizing open access licensed materials available on the Internet. This course is designed to provide students an opportunity to continue to design, develop, test, implement, manage and lead a "makerspace" project that they started in a "sister" course, SPP 597M.

A makerspace is a physical location where people gather to share resources and knowledge, work on projects, network, and build. The `Maker Culture? emphasizes learning through doing-it-yourself, or doing-it-together, in a social environment and utilizing open access licensed materials available on the Internet. This course is designed to provide students an opportunity to learn about the underpinnings of makerspaces and maker culture, and then work on a makerspace project in a team (ideally) or as an individual, if you so desire.