Date on Honors Thesis
Spring 5-3-2023
Major
Agribusiness
Minor
Data Analytics
Examining Committee Member
Jeffrey Young, PhD, Advisor
Examining Committee Member
Naveen Musunuru, PhD, Committee Member
Examining Committee Member
David Gibson, PhD, Committee Member
Abstract/Description
Food insecurity is a stark threat that grips our country and affects households throughout our country. Dietary insufficiency manifests itself in ways that affect health and public safety. According to researchers, individuals who suffer from food insecurity have a higher risk of aggression, anxiety, suicide ideation and depression. These problems tend to occur unequally distributed among those households with lower income. In this work, an exploratory analysis within these data sets will be performed to examine the socio-economic, biographical, nutritional, and geographical principal components of food insecurity among survey participants and how the US Supplemental Nutrition Assistance Program (SNAP) effects partakers of this study. Relevant statistical and algorithmic tools will be used such as Self organizing maps (SOMs) and hierarchical clustering will be used for cluster analysis in addition to logistic regression and random forests for propensity score matching. Final results show a positive effect on household wellbeing and increased food spending on SNAP participants.
Recommended Citation
Mattingly, Logan, "A Probabilistic Exploration of Food Supplementation and Assistance" (2023). Honors College Theses. 182.
https://digitalcommons.murraystate.edu/honorstheses/182
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Included in
Agribusiness Commons, Data Science Commons, Multivariate Analysis Commons, Statistical Models Commons