The National Forest Inventory and Analysis (FIA) Program of the United States Forest Service collects and analyzes data on many important forest attributes in the United States. In producing estimations, the current FIA procedure is to utilize post-stratification (PS) estimation, and the Interior West (a region of the United States) uses this estimation technique by using forest and non-forest stratification.

The purpose of our analysis is to investigate the interaction between sleep and depression frequency by sex asrisk factors for diabetes, contributing to the existing research that has established each of these risk factorsindependently. Using 2018 National Health Interview Survey data from the IPUMS database, we fit fourlogistic regression models with diabetes status as the response. Although our results in relation to sleep wereinconclusive, daily or weekly depression was found to be a significant predictor of diabetes risk, particularlyfor women.

The Austin Animal Center is the largest no-kill animal shelter in the United States. This paper uses intake and outcome data on animals entering the shelter, and looks at variables such as breed, size, and sex to predict the outcome of dogs. After dividing the data into training and testing subsets, we created a regression tree that, based on predictors such as age, size based on breed, sex, whether the animals were spayed or neutered, condition upon intake, and the time they spent in the shelter, predicts whether a dog will be adopted, returned, transferred, or has died.

The purpose of this paper is to ascertain which factors have the greatest influence over graduation rate in high schools in Chicago Public Schools (CPS). Using the 2017-2018 CPS report, with identification information, student surveys, and teacher surveys about schools within CPS, we found that mobility rate, school type, involvement of parents, attendance average, school survey safety, ambitious instruction, and culture climate rating have the most significant impact on graduation rate. Mobility rate and attendance were found to be particularly useful predictors in our model.

The Reading the Mind in the Eyes Test (RMET) is a prevalent clinical measure for social cognition and theory of mind. However, due to the exclusive use of monochromatic pictures of white individuals and unintuitive vocabulary in the questionnaire, the original RMET has been updated to include diverse, full-color photographs of male and female faces as well as simpler vocabulary. In this study, we assess whether these revisions meaningfully address identified areas of potential bias in the original RMET.

Since many people think of a college degree as one of the essential steps on the road to success, we explored the factors that may be associated with the 6-year graduation rate of U.S. colleges and universities that grant at least a bachelor's degree and are not majority online.

This project studies proportions of batted ball quality across the 2019 MLB season when facing two different types of defensive alignment. It also attempts to answer if run production is affected by shifts. Batted ball quality is split into six groups (barrel, solid contact, flare, poor (topped), poor (under), and poor(weak)) while defensive alignments are split into two (no shift and shift). Relative statistics come from all balls put in play excluding sacrifice bunts in the 2019 MLB season.

We propose a two-phase synthesis process for synthesizing income, a sensitive variable which is usually highly-skewed and has a number of reported zeros. We consider two forms of a continuous income variable: a binary form, which is modeled and synthesized in phase 1; and a non-negative continuous form, which is modeled and synthesized in phase 2. Bayesian synthesis models are proposed for the two-phase synthesis process, and other synthesis models are readily implementable. We demonstrate our methods with applications to a sample from the National Health Interview Survey (NHIS).

The COVID-19 pandemic has led to many governments taking drastic measures to keep people from infection. One of the main steps they have taken is implementing stay-at-home orders to deter the spread. The goal of our research was to see if there is a significant difference in the rate of infection between US counties before and after the order was put in place.

This project, which seeks to analyze demographics and votes of the United States Supreme Court, has 3 aims.