Large-scale data on fatal police shootings from The Washington Post’s database is available for analysis using statistical methods like p-tests. I’ll go into how p-tests could be used to draw conclusions from this dataset in this piece.P-tests are used to establish if a difference between groups that has been detected is statistically significant or more likely the result of chance. P-tests could be used in the following situations:
Evaluating racial differences in the per-capita shooting rates of Black and White victims, for example. A significant p-value might attest to the existence of true differences.Analyzing the armed state of victims in relation to several situational elements, such as location, mental illness, and flight. Significant interactions can be found using p-tests.- Examining patterns across time. Based on p-values, are quarterly shooting rate increases or declines from year to year significant?- Evaluating racial variations in the mean age of victims.
Age differences would be significant if the p-value was low.
A significance level (often 0.05) and p-value computation allow researchers to draw statistical inferences about observed differences. The null hypothesis—that there is no true difference between the groups—is rejected by significant p-values.P-testing offers a simple way to use the Washington Post data to perform thorough statistical analyses. It goes beyond straightforward explanations to explicitly test theories on variables such as ethnicity, mental health, armed status, age, and geography and draw conclusions based on facts. This enables a clearer comprehension of the causative patterns behind police shootings.