Applied Linear Statistical Models
Mario Banuelos, California State University-Fresno
In this CURE, students will use descriptive and inferential statistics through linear models on new data sets, either directly affecting the local or research community.

Using R to Build Powerful Predictive Models for Kaggle Competitions
Earvin Balderama, California State University-Fresno

Race & Incarceration in The USA Overtime: Analysis of Trends & Forecast
Shyamal Das, Elizabeth City State University
The course in Race and Ethnic Relations examines the evolving nature of America's social and cultural diversity in terms of different race and ethnic groups (Whites, Blacks, Hispanics, Asian-Americans, and American-Indians), and the issues of racial prejudice, hatred, and discrimination in the country. In so doing, students complete the final paper based on research on the relationship between race and incarceration. The research utilizes arrest data from the Bureau of Justice Statistics website. Students derive the research questions and corresponding hypotheses based on their review of literature. Based on their data analysis, they attempt to explain or interpret the arrest data on the relationship between race and the arrest rates by types of crimes. There two steps: (1) individuals complete data gathering and analysis as well as interpretation in the first place; and (2) groups will be formed by at least three students in each. The groups will prepare the final group paper and present the findings in the class. The current assignment illustrates on the Step 1 of the final project. Each student will select an assigned crime type (see the Assignment Topics) from the Bureau of Justice Statistics database, and run the graphs to show the trends by race. Assess whether students can explain the arrest rates by race. Then each student runs another analysis to forecast the arrest rates for the coming ten to fifteen years. The final group outcomes will be presented in the class. The proposed CURE incorporates a STEM component into social science as students run forecasting models for an important social problem in the USA.

Brain Mapping of Psychiatric Disorders
Chris Miller, California State University-Fresno
This course will introduce students to the neuroscience of psychiatric disorders by guiding them through the process of conducting a meta-analysis of fMRI studies of a particular psychiatric disorder of their choice.

Effect of Short Blood Sample on Patient Results Validity
Anna Marti-Subirana, Phoenix College
This CURE addresses how body fluid short sampling affects result interpretation and diagnostics. Short sampling can lead to false result interpretation and misdiagnosis. No data are available on the impact of short sampling and clinical diagnostics.

Introduction to Statistical Methods "for the CURE"
Meredith Anderson, Adams State University; Ashley Meek, Adams State University
Students will take data collected from other CURE classes and perform a variety of statistical analyses. They will learn how to prepare data sets for analysis and about experimental design. Students will see how technology facilitates the calculation of summary statistics and the visualization of data.

Emerging Contaminants in Arizona
Frank Marfai, Phoenix College

Spatial Distribution of Food Resources in the Phoenix Metro Area.
Elena Ortiz, Phoenix College
The main research question/ driving question is: How are food resources distributed across the urban landscape? Students will explore previous work on food deserts in the Phoenix Metro area, use census data, USDA data, collect and compile data on the local food system, create data visualizations and maps, and determine future data needs. Students will also determine stakeholders and community members that could act on the results of their findings and identify appropriate ways to communicate their research to those audiences.

Beyond the acronym: Employing data science to improve engagement in STEM
Pamela Reynolds, University of California-Davis
Forbes magazine ranked UC Davis as the "best value college for women in STEM." Let's investigate why, together! In this hands-on Course-based Undergraduate Research Experience (CURE), you will leverage computational tools and methodologies to explore, analyze and design solutions to maximize discoverability and engagement with STEM offerings right here at UC Davis. Community-based tools like the UC Davis STEM portal help students and members of the broader community discover and connect with opportunities in science, technology, engineering and math. How do we define STEM, and how do people interface with the diversity of offerings at our university? Through this seminar you will learn about web scraping, text mining, natural language processing, and user interface design as you work on projects to optimize search functionality and increase content management automation for the Portal, which serves as a single point of entry for catalogued information related to STEM initiatives, clubs, programs and events on campus. This research will be used to improve the discoverability and accessibility of our university's resources, and identify new opportunities for multidisciplinary research and engagement with STEM. The data we collect and workflows designed in this class will contribute to research in the digital humanities and philosophy of science regarding the shape of the discourse surrounding STEM in academia. It will also have a direct application in helping our students and broader community discover new resources and opportunities. Students will be required to work both individually and collaboratively in groups, and to share their learning with each other. This class is open to first-year freshman and transfer students from all majors. You do not need to be a computer scientist to be successful in this course, but you should be comfortable using a computer and have prior exposure to programming (R, Python, etc.). Your instructor team is looking forward to supporting your learning and engagement with research in this class!