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Poll: Jeb, Trump in virtual tie (New poll)
The HIll ^
| 7/11/15
| Mark Hensch
Posted on 07/11/2015 10:07:47 AM PDT by jimbo123
GOP presidential candidates Jeb Bush and Donald Trump are locked in a virtual tie for the 2016 Republican nomination, according to a Reuters-Ipsos poll released Saturday.
It found that 16.1 percent of self-identified Republicans back Bush, the former governor of Florida.
Trump, a New York business mogul, chases Bushs lead with 15.8 percent support.
New Jersey Gov. Chris Christie came in third 9.5 percent of possible voters backing.
Sen. Rand Paul (R-Ky.) is next at 8.1 percent, followed by retired neurosurgeon Ben Carson at 7.2 percent.
Wisconsin Gov. Scott Walker widely expected to enter the 2016 field Monday earned 5.8 percent.
(Excerpt) Read more at thehill.com ...
TOPICS: News/Current Events
KEYWORDS: 2016polls; deportjebbush
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To: jimbo123
Explain something to me. This poll was on online poll. So how does an online poll work
with regards to contacting a participant?
41
posted on
07/11/2015 11:21:06 AM PDT
by
deport
To: deport
http://polling.reuters.com About This Reuters / Ipsos poll began in January 2012 and since then continuously polled between 2,000 and 3,000 people a week. Over that period, we have asked hundreds of questions ranging from presidential politics to the Oscars, from the Syrian civil war to the perception of social networks, such as Facebook and Twitter. Unlike almost all mainstream polls, the data is entirely collected via online surveys. Online surveys allow us to collect far more data and to be more flexible and fast-moving than phone research, and online is also where the future of polling lies. This methodology may be different from the traditional (telephone) approach used by others, but it is highly accurate: It was the most accurate national poll of US residents published immediately before the November 2012 general election. Our data is primarily drawn from online surveys using sampling methods developed in consultation with several outside experts. These involve recruiting respondents from the entire population of US-based Internet users in addition to hundreds of thousands of individuals pre-screened by Ipsos. The responses are then weighted based on demographic information. Because of the volume of demographic information collected, the poll provides unprecedented insight into the myriad of communities that constitute the United States in the 21st century. This window into the population allows users to look at the polling results over time and adjust the aggregated interval of results to maintain a reasonable sample size. Those intervals are five-day rolling average as well as weekly, monthly and overall averages. The accuracy is measured using Bayesian credibility intervals. For the stats folks among you: the credibility interval assumes that Y has a binomial distribution conditioned on the parameter θ, i.e., Y|θ~Bin(n,θ), where n is the size of our sample. In this setting, Y counts the number of yes, or 1, observed in the sample, so that the sample mean (y ̅) is a natural estimate of the true population proportion θ. This model is often called the likelihood function, and it is a standard concept in both the Bayesian and the Classical framework. In the Bayesian framework, ones knowledge base is ones Prior Distribution. For the purposes of this document, θ is a proportion which assumes values between 0 and 1. This may reflect the proportion supporting a particular voter initiative or candidate. The family of prior distributions we are considering assumes a beta distribution, In effect, π(θ)~ß(a,b) is a useful representation of our prior knowledge about the proportion θ. The quantities a and b are called hyper-parameters, and are used to express/model ones prior opinion about θ. In other words, judicial choice of a and b can restate ones belief that the parameter is nearer to 25% (a=1 and b=3), near to 50% (a=1 and b=1) or nearer to 75% (a=3 and b=1). The choices of a and b also defines the shape of the probability curve, with a=1 and b=1 denoting a uniform or flat distribution. In effect, this is equivalent to believing that the true value of θ has the same chance of being any value between 0 and 1. The hyper-parameters a and b are not limited to a known constant. They too can be modeled as random quantities. This adds flexibility to the model, and it allows for data-based approaches to be considered, such as Empirical and Hierarchical Bayes. The posterior distribution in Bayesian statistics takes the likelihood function and combines it with our prior distribution. Using our prior Beta distribution, the posterior distribution is also a beta distribution (π(θ/y) ~ ß (y+a,ny+b)). It is the hyper-parameters of the prior distribution, i.e., ones knowledge base, updated using the latest survey information9. In other words, the posterior distribution represents our opinion on which are the plausible values for θ adjusted after observing the sample data. Our credibility interval for θ is based on this posterior distribution. As mentioned above, these intervals represent our belief about which are the most plausible values for θ given our updated knowledge base. There are different ways to calculate these intervals based on π(θ/y). One approach is to create an estimator analogous to what is done within the Classical framework. In this case, the credible interval for any observed sample is based on a prior distribution that does not include information from our knowledge base. This case occurs when we assume that the parameters of the beta distribution are a=1, b=1 and y=n/2. Essentially, these choices provide a uniform prior distribution where the value of θ is equally likely on the range between 0 and 1. In effect, our knowledge base is equally sure or unsure that the true value is near zero, 25%, 50%, 75% or 100%. The confidence interval is usually calculated assuming a normal distribution. However when we are measuring a proportion, and the estimate of the proportion is close to one or zero, this approach is no longer accurate. Therefore we use a logit transform of the proportion and estimate its confidence interval, then invert to calculate the confidence interval of the proportion.
42
posted on
07/11/2015 11:30:04 AM PDT
by
jimbo123
To: jimbo123
New Jersey Gov. Chris Christie came in third 9.5 percent of possible voters backing.This is unbelievable. Either they are democrats or they are just plain stupid.
43
posted on
07/11/2015 11:31:53 AM PDT
by
samtheman
(Trump/Cruz '16)
To: aquila48
I don’t get that. Jeb? No friggin way. Ted Cruz should be in the top 3.
44
posted on
07/11/2015 11:36:03 AM PDT
by
ThunderSleeps
(Stop obarma now! Stop the hussein - insane agenda!)
To: jimbo123
Thanks. I was looking around and found some info. In essence it’s just another approach to
collect data. If the parameters are accurate the data will basically be as good as a voice poll.
Again thanks.
45
posted on
07/11/2015 11:42:52 AM PDT
by
deport
To: jimbo123
once again the media gets the wrong answer to the question. time to laugh - voters are making chumps out of media. When election day rolls around it will not be Bush or Trump.
46
posted on
07/11/2015 11:47:14 AM PDT
by
q_an_a
(the more laws the less justiceHis true reco)
To: Red Steel
Re: Christie in 3rd place:
Uhuh yeah right.
Could be an indicator that Trump is sucking the wind out of the sails of all the conservatives in the race including Cruz. That lets the RINOs like Christie rise up.
I'm nervous about the affect on Cruz in an environment where the MSM/Fox dearly want him OUT OF THAT FIRST DEBATE.
To: deport
The Christie numbers are weird, so I don’t know what to think. But if it shows bad news for Bush, you gotta run with it.
48
posted on
07/11/2015 11:53:32 AM PDT
by
jimbo123
To: InterceptPoint
Something is weird about this Reuters IPSOS poll. Weird being = Reuters IPSOS. Cruz will be there. I’ve noticed over the years these clown pollster are the most wacky liberal pollsters or close to it.
To: Jim Noble
“A lot of Republicans support Bush because Republicans are not what you think they are.”
Bump! ...and well deserved, if I may add.
The old Republican=conservative has played out, but the Democrat=liberal is still very much in play.
50
posted on
07/11/2015 12:08:38 PM PDT
by
VMI70
To: jimbo123
51
posted on
07/11/2015 12:26:24 PM PDT
by
deport
To: jimbo123
52
posted on
07/11/2015 5:14:25 PM PDT
by
VerySadAmerican
(I'll vote for a democrat before I'll vote for a rino.)
To: truth_seeker
Touche! But I was closer. ;)
53
posted on
07/12/2015 3:19:50 PM PDT
by
anymouse
(God didn't write this sitcom we call life, he's just the critic.)
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