Berry's Statistical Journal

Other than doing basic statistics for the datasets, I’ve been trying to map the locations for each of the riots. The United States was easy since I could basically reuse my code from the beginning of the semester, but mapping the Indian dataset has been difficult as the geospatial files for Python are documented very well.  Outside of that, I also want to look into what types of corporations are associated with the majority of protests.

Lastly, I’ve just been revising my report on the Police Shootings data.

This week marks the second half of the semester and we’re moving on to a different dataset. The data that we’re looking at is for protests, bothe peaceful and violent, in the United States and India. I’ve only just started looking at the data, but one thing that sticks out to me is the notes column. I don’t know how successful it will be because the notes I’ve seen so far are very fact driven, but I’m curious about running a sentiment analysis on the notes.

Spring break is around the corner and I’m currently making so last minute changes to my report on the police shooting data. One thing I’m think of is creating more plots since my code currently focuses around text outputs. Other than that there’s not much going on this week.

As the deadline of the report approaches, I’ve fully switched my focus over to writing it. One thing I wanted to try and include where statistical tests, mainly to compare the different groupings I made of the states for my gun law research.

1. On the topic of gun laws, this week I’ve been looking into an interesting question: Does a lower proportion of crimes where the victims were armed with guns mean that the people who would’ve committed a crime didn’t or are they just commiting the crime but armed with something different? This was actually a question my mother asked when I talked about the data with her last weekend. I’ve been trying to answer it using the average frequency of police shootings for each gun law grouping.

This week has been very slow because we had no Tuesday classes this week. The one major change I’ve made is rather than grouping by coast I’ve decided to use predetermined regions in the US like the North East and Mid West. I’ve just been doing general statistics like mean, standard deviation, and so on this week for each of the different regions, but plan on doing something more specific. What that more specific thing is is something I’ll decide this weekend.

After finishing grouping the States by gun regulations, I compared the rates of shootings where the victim was armed with a gun between the three groups. I’ll hold off on staying the outcome until I write my report.

My new goal focuses on the Eastern United States and the Western United States. When I was looking at the map of the US I created, it seemed like the East Coast had a majority of black police shooting victims while the West Coast had a majority Hispanic and I’d like to confirm or deny this. I also noticed the West Cost shootings were more tightly grouped around major cities which I might also look into.

I’m currently in the process of researching gun laws by state. My goal is to classify each state into one of four or five categories. Some criteria I’ll be using for grouping are open carry laws and concealed carried laws including if you need a permit and at what age you can get a permit. The goal is to separate the states in a way that doesn’t leave one of the categories with only one or two entries.

Switching to a different topic, I noticed when looking at my mapping of each shooting that the East Coast and West Coast had different race distributions. On the East Coast, there was a large quantity of black people being killed while the West Coast had Hispanics as its majority. The West Coast also had more concentrated clusters of shootings, but that’s likely due to large amounts of land being undeveloped such as deserts and mountains or plains and farmlands.

This week I’ve been focusing on locational statistics. Using the longitude and latitude, I plotted each data point on a US map. I am also making a heatmap by county and state since that will be easier for me to read than my current plot.

For next week, I’ve found an external dataset containing educational data for each county in the US. This information may correlate to some of the features of the victims such as race or mental disability status. I also found Hugo’s idea of political affiliation to be very interesting and want to see if red states or states with concealed carry laws have a higher rate of police shootings involving victims armed with some kind of firearm.

The semester started this week. For MTH 522, I created this site to document my weekly work. I’ve also downloaded and begun to examine our police shootings dataset. My primary direction at the moment is to utilize the state attribute and outside data referencing each state’s population.