Overall, 64 percent of the nation thinks that Muslim Americans face a lot of discrimination, up 10 points since a survey taken in June. Half say that black Americans face a lot of discrimination, with 44 percent saying the same about Latino Americans, 25 percent about Jewish Americans and 24 percent about white Americans.
Voters who supported Hillary Clinton, however, hold distinctly different views from those who supported Trump.
Clinton supporters are most likely to see Latino, black and Muslim Americans as being targeted, with three-quarters or more saying each of those groups faces a lot of discrimination.
In contrast, Trump voters are more likely to say there’s a lot of discrimination against whites than they are to say the same about any of the other groups included in the survey. Forty-five percent of Trump voters think white people in the U.S. face a lot of discrimination, with 40 percent saying the same about Muslims. Just 22 percent, however, think that black Americans face a lot of discrimination, and just 19 percent say the same of Jews and Latinos.
Use the widget below to further explore the results of HuffPost/YouGov’s survey, using the menu at the top to select survey questions and the buttons at the bottom to filter the data by subgroups:
The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted Nov. 19-21 among U.S. adults, using a sample selected from YouGov’s opt-in online panel to match the demographics and other characteristics of the adult U.S. population.
The Huffington Post has teamed up with YouGov to conduct daily opinion polls.You can learn more about this project and take part in YouGov’s nationally representative opinion polling. Data from all HuffPost/YouGov polls can be found here. More details on the polls’ methodology are available here.
Most surveys report a margin of error that represents some, but not all, potential survey errors. YouGov’s reports include a model-based margin of error, which rests on a specific set of statistical assumptions about the selected sample, rather than the standard methodology for random probability sampling. If these assumptions are wrong, the model-based margin of error may also be inaccurate. Click here for a more detailed explanation of the model-based margin of error.