Project Title

A Spatial Analysis of Factors Influencing Beer Locations

Presenters

Academic department under which the project should be listed

RCHSS - Geography & Anthropology

Faculty Sponsor Name

Dr. Patterson, Mark

Does not require IRB review.

Abstract (300 words maximum)

This study examines the location of brewery types with socio-economic data to determine whether a relationship between these data exist, and if so, what the nature of the relationship is. We begin by compiling a database of location and type of brewery (n=6000), and then geocode the address of the breweries to produce a map showing the distribution of breweries in the U.S. Next, we overlay socio-economic data (independent variables) such as population (raw and density), income levels, and education levels, with the brewery locations (dependent variable), which allows us to conduct a geographically weighted regression (GWR) analysis. This analysis shows us which variables can be used to explain the location of the breweries. Preliminary results show that several variables have statistically significant local r^2. We conclude with a brief discussion on why some variables are statistically significant, while others are not.

Project Type

Poster

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A Spatial Analysis of Factors Influencing Beer Locations

This study examines the location of brewery types with socio-economic data to determine whether a relationship between these data exist, and if so, what the nature of the relationship is. We begin by compiling a database of location and type of brewery (n=6000), and then geocode the address of the breweries to produce a map showing the distribution of breweries in the U.S. Next, we overlay socio-economic data (independent variables) such as population (raw and density), income levels, and education levels, with the brewery locations (dependent variable), which allows us to conduct a geographically weighted regression (GWR) analysis. This analysis shows us which variables can be used to explain the location of the breweries. Preliminary results show that several variables have statistically significant local r^2. We conclude with a brief discussion on why some variables are statistically significant, while others are not.