The Question That Motivated This Study
Gun violence in the United States is not random. It clusters — by geography, by season, by circumstance. Some states have far higher rates than others. Some cities see violence spike in summer months. Some communities are hit harder than others, year after year.
The conventional wisdom points to two suspects: poverty and population. Larger cities, the thinking goes, have more violence simply because they have more people. And poorer communities, the research suggests, face structural conditions that make violence more likely.
But which one actually matters — statistically? Is it just a numbers game, or is something deeper at work? This study was designed to find out.
We combined two rich datasets — the U.S. Census American Community Survey (26 socioeconomic variables per state, 2008–2023) and the Gun Violence Archive (every recorded incident, 2014–2023) — to build a unified picture of where gun violence happens and why.
Rather than relying on simple correlation, we used rigorous statistical methods — permutation tests, bootstrap analysis, Welch's t-test — that don't require distributional assumptions and are robust to the skewed, real-world nature of violence data.
How We Built the Analysis
The study followed a careful five-step pipeline — each stage building evidence toward the central question.
Merging Two Worlds of Data
We joined gun violence incident counts with census economic data by year and state, then standardized everything into a gun violence rate per 100,000 population. This matters — without this step, states like California and Wyoming can't be fairly compared.
Testing Population First
We ran 1,000 permutations shuffling population values to ask: does population size predict gun violence rate? The answer was clear — observed correlation r = −0.052, p = 0.259. Population alone is not a significant driver.
Testing Poverty Next
The same permutation test applied to poverty rate told a very different story — p < 0.05. Poverty rate is a statistically significant predictor of gun violence rate, confirmed independently of population size.
High vs. Low Poverty Comparison
We split states into High and Low Poverty groups and compared their gun violence rates using Welch's t-test. The variability in High Poverty states (SD = 210.82) was dramatically higher than Low Poverty states (SD = 38.55) — a sign of deep instability in high-poverty communities.
Quantifying Uncertainty with Bootstrap
10,000 bootstrap samples gave us a 95% confidence interval of [11.66, 14.19] incidents per 100,000 for high-poverty states — a stable, robust estimate that doesn't rely on normality assumptions.
