Date of Award

12-2021

Document Type

Thesis

Degree Name

Master of Science In Aviation Human Factors

Department

Aeronautics

First Advisor

Deborah Carstens

Second Advisor

John Deaton

Third Advisor

Ryan White

Abstract

As the aviation industry expands and becomes commonplace in the modern world, it would behoove us to understand how the industry develops and passenger to population ratio could be a measure of that development. If called upon to identify how the aviation industry develops, one could only make suggestions as to which variables might be key in the development of the aviation industry. This study used existing socio-economic and population data from the United Nations and passenger information from the International Air Transport Association, with the aim to deepen the understanding of the relationship between socio-economic variables and the passenger to population ratio of a developed country. Both linear and multiple linear regression were used to analyze fourteen independent variables, both individually and combined, to reveal relationships and potentially form a predictive model. Fifteen countries were initially selected for this study, after cleansing and parsing of available data only fourteen were deemed appropriate. Results were measured using both R2 and p values where appropriate, with five-fold cross-validation being used on the predictive models to prevent overfitting. Overall, the results of the individual variable analyses varied from insignificant to significant and the best predictive model when the independent variables were combined had an R2 score of 0.75. At a glance, variables based on economic factors tend to yield better chance of a relationship with the dependent variable than the social factors, however, both were used in the construction of the best predictive model. Recommendations were made consisting of employing a similar study on countries in different stages of development, all countries data is available for combined, and deeper evaluation of the most significant independent variables.

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