The presidential primary isn’t over yet, but voters already have a good idea of who they think will win, according to a new HuffPost/YouGov survey.
Sixty-seven percent of all voters say Hillary Clinton has a realistic shot of taking the Democratic nomination, while just 26 percent say the same of Sen. Bernie Sanders (I-Vt.). A 59 percent majority think Donald Trump has a realistic shot of representing the Republican Party this year, compared to 36 percent for Texas Sen. Ted Cruz and just 8 percent for Ohio Gov. John Kasich.
There’s even more of a consensus among the members of each party. Seventy-two percent of Democrats and Democratic-leaning voters think Clinton can win, while 30 percent say Sanders has a chance. On the GOP side, 71 percent of Republicans think Trump has a realistic shot of winning, compared to 39 percent for Trump and 5 percent for Kasich.
Still, that doesn’t mean that voters are ready for the campaign to end. Only one-fifth of Democratic and Democratic-leaning voters want Sanders to drop out (about an equal percentage would prefer it if Clinton quit). The share of Republicans who want Trump or Cruz to drop out is capped at 15 and 18 percent, respectively.
The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted April 18-20 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.
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