Poll Math Question
#1
Posted 2007-December-03, 18:49
Candidate A=26%
Candidate B=25%
Plus or minus 4pts.
What does this mean?
A has somewhere between 22-30% and B has somewhere between 21-29%?
Does this mean A may be at 22% and B at 29%?
Other?
#2
Posted 2007-December-03, 19:29
This information is readily available if you Google "poll" and "confidence interval"
#3
Posted 2007-December-03, 19:35
so A could be at 22% and B at 29% or other?
If so my point is the media never makes this clear....in this example b could have a huge lead over A but they never say that.......
"Confidence Intervals
The Margin of Error
Even if you aren't familiar with confidence intervals, you've probably unknowingly run across them. You've probably heard the term "Margin of Error" used along with the results of a survey of, say, a presidential poll.
After polling 1000 eligible voters, the Star-Tribune Newspaper reported that 55% of Americans would vote for James Bean and 45% for John F Daniels +/- 3%.
That plus or minus disclaimer is the margin of error. In other words, the margin of error means that James Bean could be favored by as much as 58 to 42 percent (55 + 3) or as low as 52 to 48 percent (55 - 3)-- a six percentage point spread (58-52 = 6). This spread is the confidence interval. "
http://www.measuring...i/ci_instr1.php
#4
Posted 2007-December-03, 19:40
mike777, on Dec 4 2007, 04:35 AM, said:
so A could be at 22% and B at 29% or other?
If so my point is the media never makes this clear....in this example b could have a huge lead over A but they never say that.......
Correct: B is somewhere between 21% and 29%
The easiest way to understand whats going on it to picture one normal distribution centered at 25% and a second at 26%.
Damn media. How dare they presume that anyone has an education...
(In all seriousness, this gets covered in High School - Or at least it is in New York)
#5
Posted 2007-December-03, 22:33
Eg We are 95% certain that between 21% and 29% of the population favors candidate whoever. Or, if "95% certain" isn't a clear statement, maybe they should say "We have followed a procedure that 95 times out of 100 will give us an interval containing the true percentage of folks across the population favoring candidate whoever, and that procedure gave us the interval 21-29. We wish to warn our listeners that 5 times out of 100 this procedure will gives us an interval that does not contain the true percentage".
That is, of course, assuming that my guess of what they are doing is correct (the percentage certainty might not be 95 of course).
They could be clearer about the meaning of their ranges, but my real gripes about these polls lies elsewhere.
#6
Posted 2007-December-04, 02:47
A = 26%
B = 25%
but because of the uncertainty in any poll there is a confidence interval (usually 95%), and if that's plus or minus 4% this means that if not a sample but ALL people would be asked, it's possible that A = 22% and B = 29% also.
In fact we don't know the actual result of the poll if we would have asked everyone, which is basically an election. If the confidence interval is 95%, the 4% uncertainty roughly corresponds to 1.96 standard deviations in a normal distributions.
So the probability distribution of the election result of candidate A based on the poll of maybe 1000 people or so is a normal distribution with mean 26% and standard deviation of 2.0%.
Edit: numbers fixed.
This post has been edited by Gerben42: 2007-December-04, 05:48
#7
Posted 2007-December-04, 04:50
Gerben42, on Dec 4 2007, 11:47 AM, said:
So the probability distribution of the election result of candidate A based on the poll of maybe 1000 people or so is a normal distribution with mean 26% and standard deviation of 2.4%.
Gerben:
Mind explaining where you got the 5/3 value?
Its way early in the morning (and I didn't sleep well) but, the 68-95-99 rule states that
68% of observations fall within one standard deviation of the mean
95% fall within two standard deviations of the mean
99% fall within three standard deviations of the mean
#8
Posted 2007-December-04, 05:47
For 1-sided tests, 95% is 1.65 standard deviations, for 2-sided tests 95% is 1.96 standard deviations.
So your "rule" is correct (for 2-sided tests). All of the tests in my current work are 1-sided so this 5/3 value was in my head all the time.
#9
Posted 2007-December-04, 06:15
kenberg, on Dec 4 2007, 06:33 AM, said:
This is a reasonable explanation which you will find in some textbooks, but if I'm allowed to be pedantic I'll say that it's not correct.
The strict definition of the 95% confidence interval is the range of hypothetical true percentages, under which the empirical percentage which we actually found would have a likelihood above the 5% quantile.
There is an alternative procedure, the Bayesian one, which assumes some prior distribution of the true percentages and then updates this distribution facing the data. Then you can report a Bayesian confidence interval, defined as the range of percentages with a posterior likelihood above the 5% quantile.
If you use a "flat" prior (i.e. all plausible percentages are a priori equally likely) then for most practical purposes it hardly matters which procedure you use.
However, to see the difference, think of the extreme case where a particular candidate got zero votes in the poll. This may translate into a confidence interval of, say, 0% to 4%, but surely you cannot interpret that as if there was a 95% chance that the true percentage is below 4%, unless you specify a prior.
#10
Posted 2007-December-04, 08:23
helene_t, on Dec 4 2007, 07:15 AM, said:
kenberg, on Dec 4 2007, 06:33 AM, said:
This is a reasonable explanation which you will find in some textbooks, but if I'm allowed to be pedantic I'll say that it's not correct.
The strict definition of the 95% confidence interval is the range of hypothetical true percentages, under which the empirical percentage which we actually found would have a likelihood above the 5% quantile.
There is an alternative procedure, the Bayesian one, which assumes some prior distribution of the true percentages and then updates this distribution facing the data. Then you can report a Bayesian confidence interval, defined as the range of percentages with a posterior likelihood above the 5% quantile.
If you use a "flat" prior (i.e. all plausible percentages are a priori equally likely) then for most practical purposes it hardly matters which procedure you use.
However, to see the difference, think of the extreme case where a particular candidate got zero votes in the poll. This may translate into a confidence interval of, say, 0% to 4%, but surely you cannot interpret that as if there was a 95% chance that the true percentage is below 4%, unless you specify a prior.
Nothing wrong with a l;ittle pedantry! I have to go make some money being a pedant but I'll think this through later. I am sort of aware of what you describe but I'm weak on the details.
#11
Posted 2007-December-04, 08:29
hrothgar, on Dec 3 2007, 05:40 PM, said:
I teach it to my 12th graders. But I'm not at Public school. I don't believe it's in our standards (CA), but I can look it up.
#12
Posted 2007-December-04, 11:06
E.g.
A. Not taught in High School
B. Not taught as part of a Math Undergrad degree
C. Not taught in any of my official course for my math PhD (although I did audit 2 stats classes)
I did learn a little bit about the Normal Distribution in my physics courses.
For the record, my experience in aerospace, is less than 10% of engineers ever studied any stats, and a lot less actually know any stats. Of the folks I interview for my current work (stats for finance) probably 50% of the PhDs actually know even these sort of basic things...
P.S. In the spirit of being pedantic, poll results follow a bernulli distribution not a normal distribution. The key fact is that as the number of trials gets large, and the sample mean is sufficiently far away from 0 or 1, then the bernulli gets really close to the gaussian. Of course a gaussian is unbounded, and bernulli's are between 0 and 1, which is why you clearly have problems using the approximation near 0 and 1...
BTW, Ian Ayres book, Super Crunchers is a good layman's intro to a lot of this stuff and discussed polling and many other applications for statistics.
#13
Posted 2007-December-04, 11:42
Elianna, on Dec 4 2007, 05:29 PM, said:
hrothgar, on Dec 3 2007, 05:40 PM, said:
I teach it to my 12th graders. But I'm not at Public school. I don't believe it's in our standards (CA), but I can look it up.
Hey there
Quick point of clarification: When I said that this was covered in High School in New York, I was referring to 11th grade Social Studies rather than any of the Math classes.
As I recall, the Math core was very focused at progressing towards Caluclus in an efficient fashion. "Real" Statistics (as opposed to probability) never got covered.
However, the 11th Grade American history course included a combination of history, civics, and current events. Statistical literacy was probably slotted under civics...
#14
Posted 2007-December-04, 13:20
I expect an adequately, for most purposes, correct statement of 25 plus or minus four might be: We are really quite confident that the true percentage lies between 21 and 29, it's true that statistics is such that from time to time we may report intervals that are wrong, it's also true that more often then not the true answer will be somewhat closer to 25 than it will be to either 21 or 29. Probably most listener's just hear the 25, know that polls are not exact, and don't worry much about it.
Really I think a greater problem with polls is that they often ask hypotheticals. Eg If Hillary were running against Rudy and you were voting today who would you vote for? Well, Hillary is not yet running against Rudy and I am not voting today so I have not thought that through very clearly, and I strongly suspect many other people have thought it through even less. So you get numbers but not, imo, much meaning. People get overly fascinated with numbers. In my view it is not so much "what does 25 plus or minis 4 mean?" as "does the whole poll mean anything?". It has consequences, so it has meaning in that sense, but I hate to see much actually depend on it.
#15
Posted 2007-December-04, 17:55
hrothgar, on Dec 4 2007, 09:42 AM, said:
Elianna, on Dec 4 2007, 05:29 PM, said:
hrothgar, on Dec 3 2007, 05:40 PM, said:
I teach it to my 12th graders. But I'm not at Public school. I don't believe it's in our standards (CA), but I can look it up.
Hey there
Quick point of clarification: When I said that this was covered in High School in New York, I was referring to 11th grade Social Studies rather than any of the Math classes.
As I recall, the Math core was very focused at progressing towards Caluclus in an efficient fashion. "Real" Statistics (as opposed to probability) never got covered.
However, the 11th Grade American history course included a combination of history, civics, and current events. Statistical literacy was probably slotted under civics...
Yea, I was teaching a math class, but it was more a survey course, then a pre-Calculus class.
This year I'm teaching more of a pre-calculus class, so I likely won't get near covering statistics (or even probability for that matter) as the girls have not even had standards from Algebra II covered (functions, logarithms, etc). It's very frustrating.
But I bet you that my students last year could have found confidence intervals from a given poll.
#16
Posted 2007-December-04, 18:05
#17
Posted 2007-December-05, 01:50
I must say I am a bit surprised it isn't taught in some places.
Unless explicitly stated, none of my views here can be taken to represent SCBA or any other organizations.
#18
Posted 2007-December-05, 01:53
George Carlin
#19
Posted 2007-December-05, 02:44
There are quite good statistics courses at the business school and several university departments.
#20
Posted 2007-December-05, 08:07

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