Here I take the raw data from the National Crime Victimization Surveys and construct summary results missing from recent reports. Introduction The National Crime Victimization Survey is the primary source of information on criminal victimization in the United States. The survey is large and nationally representative, and each year the Bureau of Justice Statistics publishes a report summarizing the results, e.g., “
There is some really interesting stuff here. I put it in excel and converted the % to actual incidents. From what I can see it looks like during that time Blacks and Hispanics attacked more white people than victims of their own race. 1.9mm black on white attacks but only 1.4mm Black on Black attacks; 1.27m Hispanic on White attacks but 1.1mm Hispanic on Hispanic attacks. White on black was 289k incidents. Considering there are 200 million Whites and about 40 million Blacks the disproportion is pretty astounding. Do you mind if I write about that and link to this page? Am I reading that wrong?
I get that, and I appreciate this entire project. If I wanted to learn statistics of the type you do, theoretically and practically, what would you recommend doing?
The Asian numbers are difficult to credit. In 2020 there are 85,860 victimizations, and 55.9% by whites, so 47,996, and 16.6% by blacks, so 14,209.
In 2020 victimizations decline to 68,730, and 13.4% by whites, so 9,210. 56.8% by blacks, so 39,039. In other words, victimizations of Asians by whites declined fivefold, while victimizations by blacks nearly tripled.
In 2021 Asian victimizations increase to 107,990, 31.2% by whites, so 33,693, more than 3X the year before. 51.2% by blacks, so 55,615. That's pretty much the only year-on-year change in Asian victimization by race in your chart that is believable. It seems extremely unlikely that Asian victimization by whites fell by 500% in 2020 and then increased by <300% in 2021.
I understand that the figures in your chart marked by an exclamation point are based on fewer than 10 incidents, so should be interpreted with caution. But in the annual Asian victimization figures by race seem pretty dubious whether they are marked by an exclamation point or not.
Given the year-to-year fluctuations in some of the estimates because of small sample sizes, it would be useful to aggregate (or meta-analyze) the estimates across years.
There is some really interesting stuff here. I put it in excel and converted the % to actual incidents. From what I can see it looks like during that time Blacks and Hispanics attacked more white people than victims of their own race. 1.9mm black on white attacks but only 1.4mm Black on Black attacks; 1.27m Hispanic on White attacks but 1.1mm Hispanic on Hispanic attacks. White on black was 289k incidents. Considering there are 200 million Whites and about 40 million Blacks the disproportion is pretty astounding. Do you mind if I write about that and link to this page? Am I reading that wrong?
I get that, and I appreciate this entire project. If I wanted to learn statistics of the type you do, theoretically and practically, what would you recommend doing?
The Asian numbers are difficult to credit. In 2020 there are 85,860 victimizations, and 55.9% by whites, so 47,996, and 16.6% by blacks, so 14,209.
In 2020 victimizations decline to 68,730, and 13.4% by whites, so 9,210. 56.8% by blacks, so 39,039. In other words, victimizations of Asians by whites declined fivefold, while victimizations by blacks nearly tripled.
In 2021 Asian victimizations increase to 107,990, 31.2% by whites, so 33,693, more than 3X the year before. 51.2% by blacks, so 55,615. That's pretty much the only year-on-year change in Asian victimization by race in your chart that is believable. It seems extremely unlikely that Asian victimization by whites fell by 500% in 2020 and then increased by <300% in 2021.
I understand that the figures in your chart marked by an exclamation point are based on fewer than 10 incidents, so should be interpreted with caution. But in the annual Asian victimization figures by race seem pretty dubious whether they are marked by an exclamation point or not.
Given the year-to-year fluctuations in some of the estimates because of small sample sizes, it would be useful to aggregate (or meta-analyze) the estimates across years.