How This Poll Was Conducted

Here are the key things to know about this Times/Siena poll:

• Interviewers spoke with 1,695 registered voters across the country from Sept. 3 to 6, 2024.

• Times/Siena polls are conducted by telephone, using live interviewers, in both English and Spanish. About 96 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, interviewers placed nearly 194,000 calls to nearly 104,000 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 likely 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 The Times/Siena Poll is conducted, you can see answers to frequently asked questions and submit your own questions here.

Full Methodology

The New York Times/Siena College poll of 1,695 registered voters nationwide, including 1,374 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from Sept. 3 to 6, 2024. The margin of sampling error is plus or minus 2.8 percentage points for the likely electorate and plus or minus 2.6 percentage points for registered voters. Among those who completed the full survey, the margin of sampling error is plus or minus 3.2 percentage points for the likely electorate and plus or minus 3.0 percentage points for registered voters.

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 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, 96 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, 15 percent of interviews among self-reported Hispanics were conducted in Spanish, including 23 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 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 in the state, else classification based on participation in partisan primaries if available in the state, 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 1.38 for the likely electorate and 1.21 for registered voters. The design effect for the sample of completed interviews is 1.43 for the likely electorate and 1.26 for registered voters.

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.

Tech billionaire Elon Musk did not mince words when declaring his support for the Second Amendment on Sunday. 

“The right to bear arms is there to protect free speech and stop a tyrannical government from taking your rights away! That’s why the first thing that all tyrants do is disarm the people, just like Chavez did when he was first elected. After that, no more real elections in Venezuela,” Musk posted to his X account on Sunday. 

Musk was responding to an interview clip of Democratic Georgia Sen. Raphael Warnock joining NBC News on Sunday, when he was asked whether Vice President Kamala Harris should support a mandatory gun buyback program. 

Buyback programs are government initiatives to purchase privately owned firearms in order to reduce the number of guns in circulation. Harris supported such mandatory programs during her failed 2020 run for the Oval Office and has since backed away from actively supporting mandatory buyback initiatives. 

TRUMP SAYS HE’LL ASK ELON MUSK TO LEAD GOVERNMENT EFFICIENCY COMMISSION IF HE WINS ELECTION

“Should she also be, in your opinion, supporting a mandatory gun buyback program,” NBC’s Kristen Welker asked Warnock, just days after the tragic Georgia school shooting that killed four people. 

“We’re not going to be able to get where we need to go without action in Congress. We’ve got to pass some laws to deal with this. Now, I was heartened by the fact that two years ago, we finally did a gun safety law — the Safer Communities Act. And it was the first gun safety law we passed in 30 years, 30 years. And it was modest, but it did save lives, but clearly, in the wake of what happened just the other day in Winder, Georgia, is not enough,” Warnock responded. 

Musk, who has described himself as a “historically moderate Democrat,” endorsed former President Donald Trump for president earlier this year and has previously pledged his support for the Second Amendment. 

TRUMP-MUSK INTERVIEW: 5 BIGGEST TAKEAWAYS FROM THE 2024 PRESIDENTIAL ELECTION TO THE US BORDER CRISIS 

Former first lady Melania Trump joins Republican presidential nominee former U.S. President Donald Trump on stage after he officially accepted the Republican presidential nomination on the fourth day of the Republican National Convention at the Fiserv Forum on July 18, 2024, in Milwaukee, Wisconsin.  ( (Photo by Andrew Harnik/Getty Images))

“I strongly believe that the right to bear arms is an important safeguard against potential tyranny of government. Historically, maintaining their power over the people is why those in power did not allow public ownership of guns,” Musk told CNBC in 2022. 

His latest statement supporting Americans’ rights to bear arms has garnered praise from conservatives and those in the 2A community. 

TRUMP IMPERSONATES ELON MUSK TALKING ABOUT ROCKETS: ‘I’M DOING A NEW STAINLESS STEEL HUB’

Trump said last week that if he wins the election in November, he will appoint Musk to lead a government efficiency commission. 

“I will create a government efficiency commission tasked with conducting a complete financial and performance audit of the entire federal government,” Trump said in a speech Thursday at the Economic Club of New York.

The comment comes after Musk suggested the creation of a government efficiency commission last month during a conversation he hosted with Trump on X.  

“I look forward to serving America if the opportunity arises. No pay, no title, no recognition is needed,” Musk posted on X after Trump said he would follow through on Musk’s idea of establishing such a commission if he wins in November. 

Get the latest updates from the 2024 campaign trail, exclusive interviews and more at our Fox News Digital election hub.

How This Poll Was Conducted

Here are the key things to know about this Times/Siena poll:

• Interviewers spoke with 1,695 registered voters across the country from Sept. 3 to 6, 2024.

• Times/Siena polls are conducted by telephone, using live interviewers, in both English and Spanish. About 96 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, interviewers placed nearly 194,000 calls to nearly 104,000 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 likely 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 The Times/Siena Poll is conducted, you can see answers to frequently asked questions and submit your own questions here.

Full Methodology

The New York Times/Siena College poll of 1,695 registered voters nationwide, including 1,374 who completed the full survey, was conducted in English and Spanish on cellular and landline telephones from Sept. 3 to 6, 2024. The margin of sampling error is plus or minus 2.8 percentage points for the likely electorate and plus or minus 2.6 percentage points for registered voters. Among those who completed the full survey, the margin of sampling error is plus or minus 3.2 percentage points for the likely electorate and plus or minus 3.0 percentage points for registered voters.

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 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, 96 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, 15 percent of interviews among self-reported Hispanics were conducted in Spanish, including 23 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 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 in the state, else classification based on participation in partisan primaries if available in the state, 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 1.38 for the likely electorate and 1.21 for registered voters. The design effect for the sample of completed interviews is 1.43 for the likely electorate and 1.26 for registered voters.

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.