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Toplines: July 2024 Times/Siena Poll of Registered Voters Nationwide
How This Poll Was Conducted
Here are the key things to know about this Times/Siena poll:
• We spoke with 1,532 registered voters from June 28 to July 2, 2024.
• Our polls are conducted by telephone, using live interviewers, in both English and Spanish. About 93 percent of respondents were contacted on a cellphone for this poll.
• Voters are selected for the survey from a list of registered voters. The list contains information on the demographic characteristics of every registered voter, allowing us to make sure we reach the right number of voters of each party, race and region. For this poll, we placed more than 190,000 calls to more than 113,000 voters.
• To further ensure that the results reflect the entire voting population, not just those willing to take a poll, we give more weight to respondents from demographic groups that are underrepresented among survey respondents, like people without a college degree. You can see more information about the characteristics of our respondents and the weighted sample at the bottom of the page, under “Composition of the Sample.”
• The poll’s margin of sampling error among registered voters is plus or minus 2.8 percentage points. In theory, this means that the results should reflect the views of the overall population most of the time, though many other challenges create additional sources of error. When computing the difference between two values — such as a candidate’s lead in a race — the margin of error is twice as large.
If you want to read more about how and why we conduct our polls, you can see answers to frequently asked questions and submit your own questions here.
Full Methodology
The New York Times/Siena College poll of 1,532 registered voters nationwide, including 1,235 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from June 28 to July 2, 2024. The margin of sampling error is plus or minus 2.8 percentage points for registered voters and plus or minus 2.9 percentage points for the likely electorate. Among those who completed the full survey, the margin of sampling error is plus or minus 3.2 percentage points for registered voters and plus or minus 3.3 percentage points for the likely electorate.
Sample
The survey is a response rate-adjusted stratified sample of registered voters on the L2 voter file. The sample was selected by The New York Times in multiple steps to account for differential telephone coverage, nonresponse and significant variation in the productivity of telephone numbers by state.
First, records were selected by state. To adjust for noncoverage bias, the L2 voter file was stratified by statehouse district, party, race, gender, marital status, household size, turnout history, age and home ownership. The proportion of registrants with a telephone number and the mean expected response rate were calculated for each stratum. The mean expected response rate was based on a model of unit nonresponse in prior Times/Siena surveys. The initial selection weight was equal to the reciprocal of a stratum’s mean telephone coverage and modeled response rate. For respondents with multiple telephone numbers on the L2 file, the number with the highest modeled response rate was selected.
Second, state records were selected for the national sample. The number of records selected by state was based on a model of unit nonresponse in prior Times/Siena national surveys as a function of state, telephone number quality and other demographic and political characteristics. The state’s share of records was equal to the reciprocal of the mean response rate of the state’s records, divided by the national sum of the weights.
Fielding
The sample was stratified according to political party, race and region and fielded by the Siena College Research Institute, with additional field work by ReconMR, the Public Opinion Research Laboratory at the University of North Florida, the Institute of Policy and Opinion Research at Roanoke College and the Center for Public Opinion and Policy Research at Winthrop University in South Carolina. Interviewers asked for the person named on the voter file and ended the interview if the intended respondent was not available. Overall, 93 percent of respondents were reached on a cellular telephone.
The instrument was translated into Spanish by ReconMR. Bilingual interviewers began the interview in English and were instructed to follow the lead of the respondent in determining whether to conduct the survey in English or Spanish. Monolingual Spanish-speaking respondents who were initially contacted by English-speaking interviewers were recontacted by Spanish-speaking interviewers. Overall, 10 percent of interviews among self-reported Hispanics were conducted in Spanish, including 14 percent of weighted interviews.
An interview was determined to be complete for the purposes of inclusion in the ballot test question if the respondent did not drop out of the survey by the end of the two self-reported variables used in weighting — age and education — and answered at least one of the age, education, race or presidential election ballot test questions.
Weighting — registered voters
The survey was weighted by The Times using the R survey package in multiple steps.
First, the sample was adjusted for unequal probability of selection by stratum.
Second, the sample was weighted to match voter file-based parameters for the characteristics of registered voters.
The following targets were used:
• Party (party registration if available, or else classification based on a model of vote choice in prior Times/Siena polls) by whether the respondent’s race is modeled as white or nonwhite (L2 model)
• Age (Self-reported age, or voter file age if the respondent refuses) by gender (L2)
• Race or ethnicity (L2 model)
• Education (four categories of self-reported education level, weighted to match NYT-based targets derived from Times/Siena polls, census data and the L2 voter file)
• White/non-white race by college or non-college educational attainment (L2 model of race weighted to match NYT-based targets for self-reported education)
• Marital status (L2 model)
• Home ownership (L2 model)
• National region (NYT classifications by state)
• Turnout history (NYT classifications based on L2 data)
• Method of voting in the 2020 elections (NYT classifications based on L2 data)
• Metropolitan status (2013 NCHS Urban-Rural Classification Scheme for Counties)
• Census tract educational attainment
Finally, the sample of respondents who completed all questions in the survey was weighted identically, as well as to the result for the general election horse race question (including leaners) on the full sample.
Weighting — likely electorate
The survey was weighted by The Times using the R survey package in multiple steps.
First, the samples were adjusted for unequal probability of selection by stratum.
Second, the first-stage weight was adjusted to account for the probability that a registrant would vote in the 2024 election, based on a model of turnout in the 2020 election.
Third, the sample was weighted to match targets for the composition of the likely electorate. The targets for the composition of the likely electorate were derived by aggregating the individual-level turnout estimates described in the previous step for registrants on the L2 voter file. The categories used in weighting were the same as those previously mentioned for registered voters.
Fourth, the initial likely electorate weight was adjusted to incorporate self-reported intention to vote. Four-fifths of the final probability that a registrant would vote in the 2024 election was based on their ex ante modeled turnout score and one-fifth based on their self-reported intentions, based on prior Times/Siena polls, including a penalty to account for the tendency of survey respondents to turn out at higher rates than nonrespondents. The final likely electorate weight was equal to the modeled electorate rake weight, multiplied by the final turnout probability and divided by the ex ante modeled turnout probability.
Finally, the sample of respondents who completed all questions in the survey was weighted identically, as well as to the result for the general election horse race question (including leaners) on the full sample.
The margin of error accounts for the survey’s design effect, a measure of the loss of statistical power due to survey design and weighting. The design effect for the full sample is 1.22 for registered voters and 1.33 for the likely electorate. The design effect for the sample of completed interviews is 1.28 for registered voters and 1.37 for the likely electorate.
Historically, The Times/Siena Poll’s error at the 95th percentile has been plus or minus 5.1 percentage points in surveys taken over the final three weeks before an election. Real-world error includes sources of error beyond sampling error, such as nonresponse bias, coverage error, late shifts among undecided voters and error in estimating the composition of the electorate.
News
Map: 4.9-Magnitude Earthquake Shakes Louisiana
Note: Map shows the area with a shake intensity of 4 or greater, which U.S.G.S. defines as “light,” though the earthquake may be felt outside the areas shown. The New York Times
A light, 4.9-magnitude earthquake struck in Louisiana on Thursday, according to the United States Geological Survey.
The temblor happened at 5:30 a.m. Central time about 6 miles west of Edgefield, La., data from the agency shows.
U.S.G.S. data earlier reported that the magnitude was 4.4.
As seismologists review available data, they may revise the earthquake’s reported magnitude. Additional information collected about the earthquake may also prompt U.S.G.S. scientists to update the shake-severity map.
Source: United States Geological Survey | Notes: Shaking categories are based on the Modified Mercalli Intensity scale. When aftershock data is available, the corresponding maps and charts include earthquakes within 100 miles and seven days of the initial quake. All times above are Central time. Shake data is as of Thursday, March 5 at 8:40 a.m. Eastern. Aftershocks data is as of Thursday, March 5 at 10:46 a.m. Eastern.
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Donald Trump has no ‘phase two’ plan for Iran war, says US senator
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Man accused of plot to assassinate Trump testifies Iran pressured him, says Biden and Haley were other possible targets
The allegation sounded like the stuff of spy movies: A Pakistani businessman trying to hire hit men, even handing them $5,000 in cash, to kill a U.S. politician on behalf of Iran ‘s powerful paramilitary Revolutionary Guard.
It was true, and potential targets of the 2024 scheme included now-President Donald Trump, then-President Joe Biden and former presidential candidate and ex-U.N. Ambassador Nikki Haley, the man told jurors at his attempted terrorism trial in New York on Wednesday. But he insisted his actions were driven by fear for loved ones in Iran, and he figured he’d be apprehended before anything came of the scheme.
“My family was under threat, and I had to do this,” the defendant, Asif Merchant, testified through an Urdu interpreter. “I was not wanting to do this so willingly.”
Merchant said he had anticipated getting arrested before anyone was killed, intended to cooperate with the U.S. government and had hoped that would help him get a green card.
U.S. authorities were, indeed, on to him – the supposed hit men he paid were actually undercover FBI agents – and he was arrested on July 12, 2024, a day before an unrelated attempt on Trump’s life in Butler, Pennsylvania. During a search, investigators said they found a handwritten note that contained the codewords for the various aspects of the plot, CBS News previously reported.
Merchant did sit for voluntary FBI interviews, but he ultimately ended up with a trial, not a cooperation deal.
“You traveled to the United States for the purpose of hiring Mafia members to kill a politician, correct?” Assistant U.S. Attorney Nina Gupta asked during her turn questioning Merchant Wednesday in a Brooklyn federal court.
“That’s right,” Merchant replied, his demeanor as matter-of-fact as his testimony was unusual.
The trial is unfolding amid the less than week-old Iran war, which killed Iranian Supreme Leader Ayatollah Ali Khamenei in a strike that Trump summed up as “I got him before he got me.” Jurors are instructed to ignore news pertaining to the case.
The Iranian government has denied plotting to kill Trump or other U.S. officials.
Merchant, 47, had a roughly 20-year banking career in Pakistan before getting involved in an array of businesses: clothing, car sales, banana exports, insulation imports. He openly has two families, one in Pakistan and the other in Iran – where, he said, he was introduced around the end of 2022 to a Revolutionary Guard intelligence operative. They initially spoke about getting involved in a hawala, an informal money transfer system, Merchant said.
Merchant testified that his periodic visits to the U.S. for his garment business piqued the interest of his Revolutionary Guard contact, who trained him on countersurveillance techniques.
The U.S. deems the Revolutionary Guard a “foreign terrorist organization.” Formally called the Islamic Revolutionary Guard Corps, the force has been prominent in Iran under Khamenei.
Merchant said the handler told him to seek U.S. residents interested in working for Iran. Then came another assignment: Look for a criminal to arrange protests, steal things, do some money laundering, “and maybe have somebody murdered,” Merchant recalled.
“He did not tell me exactly who it is, but he told me – he named three people: Donald Trump, Joe Biden and Nikki Haley,” he added.
In 2024, multiple sources familiar with the investigation told CBS News Merchant planned to assassinate current and former government officials across the political spectrum.
Merchant allegedly sketched out the plot on a napkin inside his New York hotel room, prosecutors said, and told the individual “that there would be ‘security all around’ the person” they were planning to kill.
“No other option”
After U.S. immigration agents pulled Merchant aside at the Houston airport in April 2024, searched his possessions and asked about his travels to Iran, he concluded that he was under surveillance. But still he researched Trump rally locations, sketched out a plot for a shooting at a political rally, lined up the supposed hit men and scrambled together $5,000 from a cousin to pay them a “token of appreciation.”
He even reported back to his Revolutionary Guard contact, sending observations – fake, Merchant said – tucked into a book that he shipped to Iran through a series of intermediaries.
Merchant said he “had no other option” than to play along because the handler had indicated that he knew who Merchant’s Iranian relatives were and where they lived.
In a court filing this week, prosecutors noted that Merchant didn’t seek out law enforcement to help with his purported predicament before he was arrested. He testified that he couldn’t turn to authorities because his handler had people watching him.
Prosecutors also said that in his FBI interviews, Merchant “neglected to mention any facts that could have supported” an argument that he acted under duress.
Merchant told jurors Wednesday that he didn’t think agents would believe his story, because their questions suggested “they think that I’m some type of super-spy.”
“And are you a super-spy?” defense lawyer Avraham Moskowitz asked.
“No,” Merchant said. “Absolutely not.”
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