47th District Seat in the Florida House of Representatives

Our poll shows a close race.

But call up: It's just one poll, and we talked to but 499 people. Each candidate'southward total could hands be five points unlike if we polled everyone in the district. And having a small sample is only 1 possible source of error.

Where we called:

Each dot shows ane of the 2 three 7 nine 5 calls we fabricated.

Vote choice: Dem. Rep. Don't know Didn't answer

To preserve privacy, exact addresses accept been concealed. The locations shown here are approximate.

Explore the 2022 election in detail with this interactive map.

About the race

• Kristen Carlson is a old prosecutor and general counsel in the Florida Department of Citrus. 34% favorable rating; 16% unfavorable; 50% don't know

  Based on 499 interviews

• Ross Spano is a state representative, elected in 2012, and a lawyer. 35% favorable rating; 24% unfavorable; 40% don't know

  Based on 499 interviews

• The district runs from the inner suburbs of Tampa to Lakeland and other exurbs northeast of Tampa.

• Florida's 15th leans Republican, but Ms. Carlson has been raising more coin than Mr. Spano, and some polls take shown a shut race.

• Ms. Carlson promotes her record as a prosecutor and her legal piece of work on behalf of the land's citrus manufacture.

• Mr. Spano expresses potent support for President Trump and advocates potent curbs on illegal immigration and repeal of Obamacare.

• He opposed the express state gun restrictions passed after the mass shootings at Marjory Stoneman Douglas High in Parkland. Earlier in that debate, he was criticized for having the Florida Firm give priority to his resolution well-nigh the health risks of pornography over an assault weapons ban.

Other organizations' ratings:

Previous election results:

2016 President	+10 Trump
2012 President	+6 Romney
2016 Business firm	+15 Rep.

How our poll event changed

Equally we reach more than people, our poll volition go more stable and the margin of sampling error will shrink. The changes in the timeline below reflect that sampling fault, not real changes in the race.

1 reason we're doing these surveys live is so you tin see the doubt for yourself.

If sampling error were the only type of error in a poll, we would expect candidates who trail by 1 bespeak in a poll of 499 people to win about three out of every seven races. But this probably understates the total error past a factor of two.

Our turnout model

There's a big question on top of the standard margin of fault in a poll: Who is going to vote? It'south a especially challenging question this year, since special elections have shown Democrats voting in large numbers.

To gauge the likely electorate, nosotros combine what people say almost how likely they are to vote with information about how often they have voted in the by. In previous races, this approach has been more accurate than simply taking people at their word. Merely there are many other ways to exercise it.

Assumptions nigh 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 issue
The types of people who voted in 2014	228k	Spano +four
People whose voting history suggests they will vote, regardless of what they say	244k	Spano +two
Our estimate	244k	Spano +1
People who say they will vote, adjusted for by levels of truthfulness	265k	Carlson +1
People who say they are almost certain to vote, and no one else	279k	Carlson +6
The types of people who voted in 2016	306k	Carlson +ane
Every active registered voter	454k	Carlson +six

All estimates based on 499 interviews

In these scenarios, higher turnout tends to exist amend for Democrats.

The types of people we reached

Fifty-fifty if we got turnout exactly right, the margin of error wouldn't capture all of the fault in a poll. The simplest version assumes nosotros take a perfect random sample of the voting population. We do not.

People who answer to surveys are almost e'er likewise old, too white, too educated and also politically engaged to accurately stand for everyone.

How successful nosotros were in reaching different kinds of voters

	Called	Inter- viewed	Success rate	Our respon­ses	Goal
18 to 29	1 v 6 5	iv two	i in 37	8%	ten%
xxx to 64	1 1 vii 8 five	3 0 5	1 in 39	61%	58%
65 and older	iv v ix 1	1 5 2	i in 30	30%	32%
Male person	7 5 0 ix	2 ii 0	1 in 34	44%	45%
Female	one 0 iv iii ii	2 vii 9	1 in 37	56%	55%
White	1 1 seven 7 4	3 4 5	1 in 34	69%	67%
Nonwhite	5 three 5 8	1 three four	1 in forty	27%	28%
Cell	1 2 7 one nine	3 iii 9	ane in 38	68%	—
Landline	five 2 2 ii	1 6 0	1 in 33	32%	—

Based on administrative records. Some characteristics are missing or wrong. Many voters are chosen multiple times.

Pollsters compensate past giving more than weight to respondents from under-represented groups.

Here, we're weighting by age, political party registration, 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 instruction 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 upshot
Weight using demography information instead of voting records, like most public polls	Carlson +3
Don't weight by education, similar many polls in 2016	Carlson +1
Our estimate	Spano +1
Don't weight by party registration, similar virtually public polls	Spano +2

All estimates based on 499 interviews

Undecided voters

About fourteen per centum of voters said that they were undecided or refused to tell u.s. whom they would vote for. On questions nigh issues, these voters well-nigh closely resembled Democrats.

Issues and other questions

Do you approve or disapprove of the job Donald Trump is doing as president?

	Approve	Disapp.	Don't know
Voters due north = 499	49%	46%	5%

Would you lot prefer Republicans to retain command of the Firm of Representatives or would yous prefer Democrats to take command?

	Reps. keep House	Dems. have House	Don't know
Voters n = 499	46%	49%	5%

Percentages are weighted to resemble likely voters.

What dissimilar types of voters said

Voters nationwide are deeply divided along demographic lines. Our poll suggests divisions too. But don't overinterpret these tables. Results amid subgroups may not be representative or reliable. Be particularly careful with groups with fewer than 100 respondents, shown here in stripes.

Gender

	Dem.	Rep.	Und.
Female n = 279 / 55% of voters	46%	38%	sixteen%
Male person 220 / 45%	38%	fifty%	eleven%

Age

	Dem.	Rep.	Und.
18 to 29 n = 41 / ix% of voters	56%	19%	25%
30 to 44 eighty / sixteen%	53%	30%	18%
45 to 64 224 / 43%	38%	48%	xiv%
65 and older 154 / 33%	41%	fifty%	9%

Race and pedagogy

	Dem.	Rep.	Und.
Nonwhite n = 123 / 26% of voters	66%	eighteen%	17%
White, college grad 162 / 25%	38%	48%	fourteen%
White, non higher grad 202 / 46%	32%	57%	11%

Education

	Dem.	Rep.	Und.
H.S. Grad. or Less n = 91 / 31% of voters	40%	47%	xiii%
Some College Educ. 178 / 33%	43%	45%	12%
4-twelvemonth Higher Grad. 121 / 22%	38%	44%	18%
Post-grad. 101 / 13%	59%	29%	12%

Party

	Dem.	Rep.	Und.
Democrat n = 165 / 34% of voters	88%	3%	9%
Republican 186 / 37%	5%	89%	half-dozen%
Independent 126 / 24%	44%	31%	26%
Some other party 14 / three%	12%	41%	47%

Party registration

	Dem.	Rep.	Und.
Autonomous n = 188 / 37% of voters	84%	half dozen%	10%
Republican 216 / 42%	7%	84%	nine%
Other 95 / 21%	42%	29%	29%

Intention of voting

	Dem.	Rep.	Und.
Already voted n = 85 / eighteen% of voters	62%	33%	5%
Almost certain 291 / 59%	38%	47%	14%
Very probable 91 / eighteen%	43%	45%	12%
Somewhat probable 16 / iii%	32%	32%	36%
Not very probable 6 / one%	12%	—	88%
Not at all likely 6 / 0%	15%	64%	21%

Percentages are weighted to resemble probable voters; the number of respondents in each subgroup is unweighted. Undecided voters includes those who refused to answer.

Other districts where we've completed polls

California 48 Orange County	Sept. four-6
Illinois 12 Downstate Illinois	Sept. 4-6
Illinois 6 Chicago suburbs	Sept. four-vi
Kentucky 6 Lexington surface area	Sept. 6-8
Minnesota 3 Minneapolis suburbs	Sept. 7-9
Minnesota 8 Iron Range	Sept. half dozen-9
West Virginia three Coal Country	Sept. 8-10
Virginia 7 Richmond suburbs	Sept. nine-12
Texas 23 S Texas	Sept. 10-11
Wisconsin 1 Southeastern Wisconsin	Sept. 11-xiii
Colorado six Denver Suburbs	Sept. 12-14
Maine 2 Upstate, Down Due east Maine	Sept. 12-fourteen
Kansas 2 Eastern Kansas	Sept. xiii-fifteen
Florida 26 S Florida	Sept. thirteen-17
New Mexico 2 Southern New Mexico	Sept. 13-18
Texas 7 Houston and suburbs	Sept. 14-18
California 25 Southern California	Sept. 17-19
New Bailiwick of jersey 7 Suburban New Jersey	Sept. 17-21
Iowa one Northeastern Iowa	Sept. xviii-xx
California 49 Southern California	Sept. 18-23
Texas 32 Suburban Dallas	Sept. nineteen-24
Pennsylvania 7 The Lehigh Valley	Sept. 21-25
Kansas 3 Eastern Kansas suburbs	Sept. twenty-23
California 45 Southern California	Sept. 21-25
New Jersey three South, central New Jersey	Sept. 22-26
Nebraska 2 Omaha expanse	Sept. 23-26
Washington eight Seattle suburbs and across	Sept. 24-26
Michigan 8 Lansing, Detroit suburbs	Sept. 28-October. 3
Virginia 2 Littoral Virginia	Sept. 26-Oct. i
Arizona 2 Southeastern Arizona	Sept. 26-Oct. one
Iowa 3 Southwest Iowa	Sept. 27-30
Ohio one Southwestern Ohio	Sept. 27-Oct. 1
Minnesota 2 Minneapolis suburbs, southern Minn.	Sept. 29-Oct. 2
Michigan eleven Detroit suburbs	Oct. 1-six
Illinois 14 Chicago exurbs	October. 3-8
Northward Carolina ix Charlotte suburbs, southern Due north.C.	Oct. 1-5
New York one Eastern Long Island	Oct. iv-8
Texas 31 Central Texas, Round Rock	Oct. 1-5
Northward Carolina thirteen Piedmont Triad	Oct. 3-8
Pennsylvania 16 Northwestern Pa.	October. v-8
Texas Senate The Lone Star State	Oct. 8-eleven
Tennessee Senate The Volunteer State	Oct. viii-11
Nevada Senate The Silverish State	Oct. 8-10
Pennsylvania 1 Delaware Valley	October. 11-14
Arizona 6 Northeastern Phoenix suburbs	Oct. 11-fifteen
Minnesota 8 Fe Range	Oct. xi-14
Virginia 10 Northern Virginia	Oct. 11-15
Colorado half-dozen Denver Suburbs	Oct. 13-17
Washington three Southwest Washington	Oct. xiv-nineteen
Texas 23 South Texas	Oct. 13-18
West Virginia iii Coal Country	October. fourteen-18
Kansas iii Eastern Kansas suburbs	Oct. fourteen-17
Arizona Senate The Grand Canyon State	Oct. 15-19
Florida 27 South Florida	Oct. 15-19
Maine 2 Upstate, Downwards East Maine	Oct. 15-eighteen
New Jersey 11 Northern New Jersey suburbs.	October. thirteen-17
Pennsylvania eight Wyoming Valley	Oct. 16-19
Florida 15 Tampa Exurbs	Oct. 16-19
Virginia 5 Central, southern Virginia	Oct. 16-22
California 39 E of Los Angeles	Oct. 18-23
Illinois 12 Downstate Illinois	Oct. xviii-22
Virginia two Coastal Virginia	Oct. xviii-22
California 49 Southern California	October. 19-24
Florida 26 South Florida	Oct. xix-24
Texas 7 Houston and suburbs	Oct. 19-25
Illinois 13 Downstate Illinois	Oct. 21-25
New Mexico 2 Southern New Mexico	Oct. 19-23
Illinois 6 Chicago suburbs	Oct. twenty-26
Ohio i Southwestern Ohio	October. 20-24
California 10 Fundamental Valley farm chugalug	Oct. 21-25
New Bailiwick of jersey 3 South, fundamental New Bailiwick of jersey	Oct. 21-25
Pennsylvania 10 Due south, central Pennsylvania	Oct. 23-26
New York xi Staten Island, southern Brooklyn	Oct. 23-27
Florida Senate The Sunshine State	October. 23-27
Florida Governor The Sunshine State	October. 23-27
Utah 4 South of Table salt Lake Urban center	Oct. 24-26
New York 27 Western New York	October. 24-29
Iowa 3 Southwest Iowa	Oct. 25-27
California 25 Southern California	October. 25-28
California 45 Southern California	October. 26-Nov. one
Pennsylvania 1 Delaware Valley	Oct. 26-29
Northward Carolina ix Charlotte suburbs, southern N.C.	Oct. 26-thirty
Kansas 2 Eastern Kansas	October. 27-30
New Jersey 7 Suburban New Bailiwick of jersey	October. 28-31
Georgia 6 Northern Atlanta suburbs	Oct. 28-November. 4
Iowa 1 Northeastern Iowa	Oct. 28-31
Texas 32 Suburban Dallas	October. 29-November. 4
California 48 Orange Canton	Oct. 29-Nov. four
Virginia 7 Richmond suburbs	Oct. xxx-Nov. 4
Illinois 14 Chicago exurbs	Oct. 31-Nov. iv
Washington eight Seattle suburbs and beyond	Oct. 30-Nov. iv
Iowa 4 Northwestern Iowa	October. 31-November. 4
Michigan 8 Lansing, Detroit suburbs	October. 31-Nov. 4
Kentucky 6 Lexington expanse	November. i-4
New York 19 Catskills, Hudson Valley	Nov. 1-4
New York 22 Central New York	Nov. ane-4

About this poll

• Nearly responses shown hither are delayed near 30 minutes. Some are delayed longer for technical reasons.
• The design effect of this poll is one.17. That'due south a measure of how much weighting we are doing to make our respondents resemble all voters.
• Read more than most the methodology for this poll.
• Download the microdata behind this poll.

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

Data drove by Reconnaissance Marketplace Research, M. Davis and Visitor, the Institute for Policy and Opinion Enquiry at Roanoke Higher, the Survey Enquiry Eye at the University of Waterloo, the University of North Florida and the Siena Higher Research Plant.

By Michael Andre, Larry Buchanan, Matthew Bloch, Jeremy Bowers, Nate Cohn, Alastair Coote, Annie Daniel, Richard Harris, Josh Katz, Rebecca Lieberman, Blacki Migliozzi, Paul Murray, Adam Pearce, Kevin Quealy, Eden Weingart and Isaac White

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Source: https://www.nytimes.com/interactive/2018/upshot/elections-poll-fl15-3.html?module=inline

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