Monday – November 1,2023.

My group and I have decided to undertake these tasks, and we have divided the following tasks among ourselves.

Akshit:

1. Data Collection: Coordinate with Gary to obtain location data from police stations. This initial step involves working with Gary to gather geographical information on police stations, including their latitude and longitude coordinates. Accurate location data is crucial for subsequent analysis.
2. Distance Calculation: Once we have the police station coordinates, the next step is to calculate the distances between these police stations. This step is essential for understanding law enforcement’s spatial distribution and coverage in the area under consideration.
3. Demographic Analysis: To gain a deeper understanding of the dataset, we will analyze data related to race, age, and shooting incidents. Our goal is to determine which areas experience the highest frequency of shootings. This analysis will help identify any potential hotspots.
4. Proximity Analysis: Investigate how far shooting incidents occur from the police stations. This analysis will shed light on response times and potential areas where increased law enforcement presence may be required.
5. Data Segmentation: To develop and validate our analysis, we will segment the data into training and testing datasets. Considering population distribution in this process is crucial to ensure our models are representative and can make accurate predictions or classifications.

Parag:

1. Combination Analysis: In parallel with Akshit’s work, I will conduct a combination analysis. This involves considering variables such as “armed_with” and “flee_status” alongside other relevant factors from the dataset. The goal is to identify potential patterns or correlations among these variables and their impact on shooting incidents.
2. Summary Statistics: I will generate basic summary statistics to gain initial insights into the dataset. These statistics will provide an overview of the data, including measures like means, medians, and standard deviations for critical variables. This step will help us identify trends and outliers.
3. ANOVA Test: To assess the impact of different variables on the data, I will perform an analysis of variance (ANOVA) test. This statistical test will help us understand if significant differences exist between groups or categories within the dataset, particularly when considering factors like age, race, or other relevant variables.
4. Grouping and Trend Analysis: I will group the data by age and race to identify trends and patterns in the analysis. This step aims to uncover any disparities or patterns related to age and race concerning shooting incidents. It can help inform potential policy recommendations or interventions.

Combining Akshit’s geographic and demographic analysis with Parag’s statistical and variable-focused analysis, we aim to comprehensively understand the factors contributing to shooting incidents, their locations, and potential strategies for improving public safety in the areas under investigation.