This project aims to test the hypothesis if geography has an impact on anxiety of an individual. In this particular situation, the spatial analysis is conducted in the Metrotech Commons area, an urban plaza which houses school buildings, cafes, restaurants, as well as industrial buildings. Any or all of these could be a factor in influencing such emotions in an individual. Furthermore, the project performs spatial autocorrelation using Morans I and Anselin Local Moran's I, thus calling for a good understanding of the underlying theory.

Procedurally the data observations were collected only during the day when there was a significant proportion of the population in the MetroTech Commons, considering that most of the classes run during the day time, it was much more efficient to thus collect the data at that time. There were 5 distinct data observations that were taken on Tuesdays, Wednesdays and Thursdays for two weeks for one particular hour (9:00 AM - 10:00 AM) that resulted in a significant number of observational points. A few data observations were also collected during night time and also during Thanksgiving and Black Friday, however, the data was not sufficient enough, as it lacked observational points.Thus this data was not considered during the plotting and testing phase of this project, as it would significantly change results and testing results. Of all the data, only a small portion was then used in the analysis, this is due to the fact that this project considers facial expressions as an underlying observational limitations. Thus, only those individuals are considered which demonstrated a facial expression which could help me to determine if they feel anxious or not.
Photos, as well as video recordings, were taken to keep a track of the individuals and their locations, with the help of iPhone, with 0.5x wide angle lens, thus allowing to collect more data from eleven positions in the metrotech commons. However, not all individuals in the plots carry a geocoordinate, they are added to the data set relative to their positioning to the created grid structure in ArcMap. The data collection required a significant period of observation to get a gist of the current movement period.

We can see clustering that has been verified statistically using Morans I, and to talk about the observation it is probable that individuals that fall in the cells that lie around the school building can be more anxious than others who may be sitting in the triangular section of the area, or someone who is talking a walk with a dog. The triangular area sees a cooler effect in terms of anxiety, this is straightforward, as a student if I am stressed about something, I’d rather go straight to the library to get my work done, instead of taking a shortcut through the central part of the area. The other factors that might influence the considered assumption of this project on emotional expressions is the directional flow of an individual in the grid, are they leaving the building or entering it, which is thus not considered, and thus can be extended beyond the scope of this project.