Given expectations, our poll is a good result for Republicans. It’s just one poll, though.

Can a Republican moderate hold a majority Hispanic district in Texas? We made 38789 calls, and 488 people spoke to us.

This survey was conducted by The New York Times Upshot and Siena College.

Hey, I’m Alex Burns, a politics correspondent for The Times. I’ll give you the latest reporting and intel on the midterms and take your questions from the campaign trail.

It’s generally best to look at a single poll in the context of other polls:

On paper, this is a classic battleground district. But the Cook Political Report rates it as ‘lean Republican,’ in part because Mr. Hurd has distinguished himself from the national party. The district also reflects a broader pattern of Democrats’ struggles to match their presidential-year tallies in majority Hispanic areas.

Mr. Hurd wrote a New York Times op-ed in July asserting that the president had been manipulated by Russian intelligence.

(We polled this district from Sept. 10-11. Mr. Hurd had a modest lead in that poll.)

This majority Hispanic border district stretches along the Rio Grande to the suburbs of San Antonio. Historically, it has some of the lowest turnout in the country.

is the current representative, a member of the House intelligence committee and a former C.I.A. officer. He voted against the Republican bill to repeal and replace the Affordable Care Act. 58% favorable rating; 26% unfavorable; 16% don’t know

is a former Air Force intelligence officer who worked as a director in the office of the U.S. Trade Representative. 37% favorable rating; 41% unfavorable; 22% don’t know

Each dot shows one of the 38789 calls we made.

But sampling error is not the only type of error in a poll.

One reason we’re doing these surveys live is so you can see the uncertainty for yourself.

As we reach more people, our poll will become more stable and the margin of sampling error will shrink. The changes in the timeline below reflect that sampling error, not real changes in the race.

Our turnout model There’s a big question on top of the standard margin of error in a poll: Who is going to vote? It’s a particularly challenging question this year, since special elections have shown Democrats voting in large numbers. To estimate the likely electorate, we combine what people say about how likely they are to vote with information about how often they have voted in the past. In previous races, this approach has been more accurate than simply taking people at their word. But there are many other ways to do it. Assumptions about who is going to vote may be particularly important in this race. Our poll under different turnout scenarios Who will vote? Est. turnout Our poll result The types of people who voted in 2014 120k Hurd +22 People whose voting history suggests they will vote, regardless of what they say 158k Hurd +16 Our estimate 159k Hurd +15 People who say they will vote, adjusted for past levels of truthfulness 174k Hurd +13 The types of people who voted in 2016 212k Hurd +13 People who say they are almost certain to vote, and no one else 229k Hurd +6 Every active registered voter 393k Hurd +4 In these scenarios, higher turnout tends to be better for Democrats. Just because one candidate leads in all of these different turnout scenarios doesn’t mean much by itself. They don’t represent the full range of possible turnout scenarios, let alone the full range of possible election results.

The types of people we reached Even if we got turnout exactly right, the margin of error wouldn’t capture all of the error in a poll. The simplest version assumes we have a perfect random sample of the voting population. We do not. People who respond to surveys are almost always too old, too white, too educated and too politically engaged to accurately represent everyone. How successful we were in reaching different kinds of voters Called Inter-

viewed Success

rate Our

respon­ses Goal 18 to 29 3 1 8 3 2 2 1 in 145 5% 9% 30 to 64 1 7 7 3 1 2 8 3 1 in 63 58% 58% 65 and older 6 1 4 8 1 8 3 1 in 34 38% 33% Male 1 1 9 1 7 2 4 3 1 in 49 50% 47% Female 1 5 1 4 8 2 4 5 1 in 62 50% 53% White 1 1 0 7 8 2 7 1 1 in 41 56% 45% Nonwhite 1 4 7 5 2 1 9 4 1 in 76 40% 50% Cell 1 9 9 6 4 3 1 5 1 in 63 65% — Landline 7 1 0 1 1 7 3 1 in 41 35% — Pollsters compensate by giving more weight to respondents from under-represented groups. Here, we’re weighting by age, primary vote, gender, likelihood of voting, race, education and region, mainly using data from voting records files compiled by L2, a nonpartisan voter file vendor. But weighting works only if you weight by the right categories and you know what the composition of the electorate will be. In 2016, many pollsters didn’t weight by education and overestimated Hillary Clinton’s standing as a result. Here are other common ways to weight a poll: Our poll under different weighting schemes Our poll result Don’t weight by primary vote, like most public polls Hurd +14 Don’t weight by education, like many polls in 2016 Hurd +15 Our estimate Hurd +15 Weight using census data instead of voting records, like most public polls Hurd +16 Just because one candidate leads in all of these different weighting scenarios doesn’t mean much by itself. They don’t represent the full range of possible weighting scenarios, let alone the full range of possible election results.