Graduation Year

2024

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Mathematics

Second Department

Psychology

Reader 1

Christina Edholm

Reader 2

Jennifer Groscup

Reader 3

Jennifer Ma

Abstract

The complex relationships between dog characteristics and human characteristics have long interested psychologists, with research revealing how dog breeds, attachment styles, personality traits, and other traits may predict certain dynamics between a dog and its owner. Although these aspects have been analyzed individually, there is yet to be a comprehensive analysis that aims to look at how all these traits interact with each other to impact the strength of a dog-owner relationship. Using a Bayesian network, this study aimed to model the dependencies among these variables to predict which most influence the dog-owner bond. Data were collected from a pool of participants who completed an online survey consisting of multiple validated questionnaires to measure the variables of interest, some of which included measurements of attachment styles and measurements of personality traits. It was found that similar traits between dogs and their owners lead to a higher likelihood of a strong dog-owner relationship. A computer algorithm attempted to find the model that best represented the relationships between the variables. This algorithm proposed a model that linked the owner's attachment styles and the owner's personality traits on one graph, and the dog's personality traits with the dog-owner relationship variables on another graph. This research could help to motivate better procedures in shelters where both dogs and adopters would be analyzed to find ideal pairings, ultimately reducing shelter return rates and keeping dogs out of shelters.

Additional Files
Erin Thesis Exemption Form.pdf (335 kB)
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This thesis is restricted to the Claremont Colleges current faculty, students, and staff.

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