Teaching Discriminant Analysis: Uncovering Characteristics Common to Outbound Tourism Destination Selection of Saudi Arabia Citizens

Keywords: discriminant analysis, tourism geography, Saudi Arabia, outbound
Abstract Type: Poster Abstract

Abstract

Discriminant Analysis (DA) is useful for classifying cases into mutually exclusive groups; it is the logical choice when a data set has one categorical grouped variable that is influenced by two or more continuous, interval, or count variables that are independent. Teaching statistical methods is most successful in an applied format, especially when data are relatable. Tourism exemplifies such intelligibility; despite a hiccough during the Covid-19 pandemic, tourism continues to emerge as a prominent and influential growth industry at a global scale. Published worldwide tourism data are commonly aggregated, and often distinguish such movement as inbound or outbound, with the latter focusing on citizens and/or residents of a country traveling across an international border for tourism purposes. Saudi Arabia has vibrant outbound tourism activity; tourism data on ages, incomes, education levels, and employment statuses of the country’s outbound tourism population for the year 2015 provide a unique means to assess if certain characteristics are common to Saudi citizens’ international destination choices. Performing DA with relatable data allows students to grasp its purpose, to see the immediate applicability of this statistical method, and to report and interpret the results of that analysis. The resultant linear functions produced by DA provide a means to identify motivations of travel inherent within the data, thereby demonstrating qualitative dimensions that further our understanding of Saudi outbound travelers.