Blog Post 2

Introduction

As I've continued to work on my research project on how the inclusion of a large shopping center changes the robustness by measuring changes in tax revenue, I would like to explain how and why I picked this topic. This topic was inspired and chosen largely because I live in and served on the Youth Commission of the City of Lone Tree. Lone Tree's revenue is largely based on the Park Meadows Mall, and I wanted to see if this made the city more or less stable in times of economic Unrest. Through the narrowing down of my research, I am no longer analyzing Lone Tree, due to it being too small population-wise, but I am still excited to see how my findings affect the city I call home.

PRogress

I mostly been selecting and sorting my data, and collecting the data I need to run my tests. I had to choose 60 cities because a sample size over 25 is statistically significant, so I would be able to group them and still have some buffer. I selected these cities and split them into the cities with and without large shopping centers (>30% revenue coming from a single area). That process took a lot longer than expected, and now I am working on collecting all the revenues from 2005 to 2025 for the cities listed above.

(The image pictured on the left is of the western United States, which is the area I chose to analyze, based on random selection)

Challegnes

The main challenges that I have had through this data collection period is me underestimating the time that these data collection processes would take. I assumed that splitting the 2 cities into their groups (large shopping center), would take at most 2 weeks; it took me about 4 and a half weeks. Another setback I have had was actually this week, I forgot to take all the city tax revenues for the year, so now I have to do that this upcoming week.

The image pictured on the right is from the San Jose financial department shows the spread of revenue based on sources which helped me group san Jose

Data Trends and Visualisation

Right now, because I'm only sorting my data and not yet able to graph and analyze trends, I can't provide any meaningful analysis, but this will be fixed as soon as I begin data analysis and graphing. But through the data, I have noticed that smaller cities, or cities with large college towns, or cities that are dominated by tourism, tend to have large shopping centers or areas where sales tax revenue exceeds 20%.

Reflection

The biggest thing that I have learned through this reasearch process is that I need to start better assessing how long things will take. At the start of this project, I thought that it in total would take me 2 weeks to get where I am now, and I realized that sorting through documents and double-checking things takes significantly longer than I initially assumed. I also learned that I need to better account for all things needed to start a step before going headfirst into it, like I did this week with graphing without having all my data set. So in conclusion, although I am not behind on where I should be, I am compared to my original hasty timeline, so I need to better plan things out with room for checking and mishaps in the future.

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