(Huge) delegate vote anomaly in Alabama verified

[drummergirl]

People keep saying that the demographic argument is dead. With this graph in mind, tell me why that is.

Because the charts with the straight sloped lines are anomalous. If these slopes are what is to be expected because of demographics, we should see them consistently. We don't. For instance, there are only 2 anomalous counties in Nevada (of course, they represent over 70% of the total votes), but the remaining counties have nice normal mathematics. Historical data (alabama 2008, New Hampshire back into the 90s, etc.) follow the early noise then flat line at a percentage expected pattern. Why would "demographics" be at work only in certain places and not others. The latest is Outagamie county in Wisconsin (posted by Ron Rules on the other thread) other demographically and politically similar counties are flipping like pancakes at the ihop, but not Outagamie county.

This was really put to bed about six weeks ago here : http://www.ronpaulforums.com/showth...ote-against-Ron-Paul-in-South-Carolina/page99

and is abbreviated in the technical addendum here p.29-37 https://docs.google.com/document/d/1EokVx9tDsrjAJ-7H9XoPv3KmZYDvVjSFJ4cuxJTo1iE/edit

but I think it is worth repeating for the newcomers even though it's a little long. If you don't understand the math, please read the relevant parts of the tech addendum before questions. Here is the series Liberty1789 did for the counties of South Carolina (for those interested in the county level demographics there were numerous maps posted in the above thread; look them over if you like)

 

[drummergirl]

 

[dsw]

OK- Your red graph line is distorting the sharpness of the elbow but looks like you've done it. Your "straight" line is way off. If there's any way to distort the natural sharpness of the elbow any more than you have, I'd be shocked.

I'm not sure what you mean. The red line is the data. The "straight" lines actually are straight. With my data it only starts to look like an elbow with the y-axis compressed, and with the linear overlays. Plot it without compressing the y-axis, and without the linear overlays, and it's the first graph I posted. If there really is an elbow then my calculation is wrong. I'll append the data below, with x and y values scaled by 100,000 and 1000 respectively to match your graph.

If I've got the data wrong, could you perhaps append your own data points for that original #2 graph (or for that matter, any other delegate scoring method you think is more clear as long as the calculation method is clear)? I want to be sure I understand what's going on around that 300,000 point, with data I can replicate, before getting deeper into your analysis.

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4.58788, 14.4002777778
4.60124, 14.5351666667
4.6146, 14.5261666667
4.62798, 14.6666111111
4.64142, 14.7617222222
4.65491, 14.8588888889
4.66843, 14.9558333333
4.68207, 14.9965
4.69579, 15.0158333333
4.70953, 15.0229444444
4.72346, 15.3309444444
4.73741, 15.4267222222
4.75141, 15.4143888889
4.7655, 15.5152222222
4.77965, 15.5786111111
4.79396, 15.6520555556
4.80837, 15.7883333333
4.82279, 15.8955
4.83733, 15.9909444444
4.85192, 16.0939444444
4.86657, 16.3196666667
4.88141, 16.4916666667
4.89642, 16.5978333333
4.9116, 16.5509444444
4.92699, 16.5923333333
4.94247, 16.9575
4.95801, 16.9417222222
4.97362, 17.2235
4.98929, 17.3282222222
5.00518, 17.4108888889
5.02108, 17.5067222222
5.03699, 17.6870555556
5.05295, 17.7644444444
5.06901, 17.73
5.08508, 17.7691111111
5.10118, 17.9225555556
5.11728, 18.2572777778
5.13343, 18.348
5.14973, 18.3560555556
5.16609, 18.3221111111
5.18291, 18.3886111111
5.19974, 18.5835555556
5.21661, 18.7804444444
5.23348, 19.0343888889
5.25042, 19.142
5.26743, 19.2558888889
5.28447, 19.4403888889
5.3016, 19.4451666667
5.31874, 19.5598333333
5.33599, 19.6006666667
5.35332, 19.7729444444
5.37068, 19.9007777778
5.38843, 20.0347222222
5.40672, 20.1298333333
5.42537, 20.1114444444
5.44453, 20.4510555556
5.46399, 20.4484444444
5.48397, 20.6762777778
5.50398, 20.7580555556
5.52412, 20.9785555556
5.54461, 21.1073333333
5.56534, 21.3353333333
5.5863, 21.4079444444
5.60828, 21.6375555556
5.63065, 21.6405
5.65319, 21.9128333333
5.67597, 22.1199444444
5.70755, 22.4641111111
5.74065, 22.5589444444
5.77559, 22.822
5.82875, 23.2131666667

 

[drummergirl]

So, if demographics explains all the sloped lines, like Horry, SC, then how does demographics explain all the flat lines, like Kershaw, SC?

 

[drummergirl]

Thanks for the ad-hominem. I have advanced degrees in science and mathematics.

Then presumably you can read and do simple statistics.

https://docs.google.com/document/d/1EokVx9tDsrjAJ-7H9XoPv3KmZYDvVjSFJ4cuxJTo1iE/edit

This is the cliff notes version. If you have some critique that's deeper than, "that's a crock", please use your brain cells and do something useful. Go ahead, find scientific evidence for your case. I dare you. Heck, I'll triple dog dare you.

Otherwise, we have more trolls than bridges, so you may need to find housing elsewhere.

 

[dsw]

Because the charts with the straight sloped lines are anomalous. If these slopes are what is to be expected because of demographics, we should see them consistently. We don't. For instance, there are only 2 anomalous counties in Nevada (of course, they represent over 70% of the total votes), but the remaining counties have nice normal mathematics. Historical data (alabama 2008, New Hampshire back into the 90s, etc.) follow the early noise then flat line at a percentage expected pattern. Why would "demographics" be at work only in certain places and not others.

BTW, did someone come up with the full 2008 data? I only saw the one county, Baldwin I think.

In any case, there are two arguments being made here, and I'm only trying to respond to one of them. It's sometimes argued that the graph (the other kind, not the latest one TheMan posted) should flatten out for purely statistical reasons, which would only make sense if the sample represented by the first 25% of the vote, with precincts sorted by total votes cast, is very close to being demographically equivalent to the overall sample. And various people have argued that in various ways. In the thread you just pointed me to, someone replies to an objection by saying that the precincts sorted by size are going to be scattered all over the state, and I've been told that before. But when I ran the data on Alabama ... not true. (It wasn't true in Va Beach City either, BTW.) By the time you get to the right hand side of the graph you're looking at precincts that are twice as likely to come from a few very large counties than precincts at the left side of the graph. Why would it be surprising for there to be demographic differences, that could be reflected in %vote, between the left-hand counties and the right-hand counties, and a correlation between %vote and total votes cast?

And if there is such a correlation, what happens to this argument from the thread you just pointed me to?

And if you tell me that Romney has got 50% of the votes in that ballot, I can tell you that he needs to be real close that 50% by the time we have counted 90% of the votes, a bit less close at 80%, etc... Poll science shows that 10/20% might suffice for the oscillator to turn into a complete flat line. But maths allow another nice trick as well. If you tell me after 25% of the votes counted what Romney's score is, I can actually tell you the probability that he will get to a score of 50% at the end of the vote tally. Isn't hypergeometry nifty?

As we have seen, Romney's lines do not converge flatly towards the final result. It does not everytime the ballot is relevent to the final outcome. His score starts by oscillating and flattening but then shoots up in a straight line in dozens of counties. That is mathematically impossible.

"And if you tell me that Romney has got 50% of the votes in that ballot, I can tell you that he needs to be real close that 50% by the time we have counted 90% of the votes," ... only if that ballot sample is statistically random. If you know that your sample is unbiased (or if you are analyzing an exit poll and you massage the data, as they do, to try to approximate a random sample based on the demographics of your samples and the demographics your model predicts for the overall turnout) then and only then can you predict the expected error.

If Romney has got 50% of the vote in a sample and the demographics for that sample are different from the overall demographics, the math does not work that way. If the precincts counted on the left side of a cumulative graph are different demographically than the precincts further to the right, then (assuming that different demographic segments may vote in different ways, but presumably we agree on that) then the graph may or may not flatten out.

Back to your question: Why would "demographics" be at work only in certain places and not others.

That's not a mathematical question, it's an empirical question. And an interesting one, but any time I start responding to the empirical question the (bogus) mathematical argument comes up as a reply. So I'd like to make some progress on the mathematical question first, then come back to he other one.

Two questions:

Do you agree that the marble drawing analogy, and the math that works in that kind of situation, does not apply if the initial sample might be biased in some way? Strictly as a math question.

If we agree on that, then do you agree that the demographics of the more densely-populated counties in a state may reasonably be expected to *possibly* differ demographically from the more sparsely-populated counties in a state? Just as a general question about voter demographics, not about anything else.

 

[affa]

The vertical blue line separates the precincts that come before the 300,000 "crime happens here" point from the ones that come after. Now I'm not clear on what flipping theory says would be done to the votes at each precinct, but it's a small number of points (with big vote counts) that are doing a lot of the work here.

You're missing the point. The Man's charts are charting Romney votes - Romney Delegate Votes.
I'll say that again: Romney votes - Romney Delegate Votes.

At 300k he suddenly starts gaining votes at a significantly different pace AGAINST HIMSELF.

As The Man said, "The rate at which Romney received new precinct votes increases by 4.2% (of the overall votes cast) at vote count 300k, or precinct votes cast = 850."

We're seeing the same sudden increase in Romney votes at a specific point in cumulative vote totals, but here? We have the holy grail of benchmarks - Romney's own delegate performance. He suddenly starts out performing his own delegates as his 'candidate' votes shift into high gear while his delegate votes trail behind. This is (one of several reasons) why The Man's newest charts are important. For you to suddenly try to hide behind demographics again is plain silly, unless you're positing some magical demographic that suddenly kicks in to vote for Romney while this same demographic magically ignores his delegates. I

It fits perfectly with the flipping theory. Clean as a whistle. If Romney's votes get magical at 300k, but they did not touch the delegates, then you'd see exactly this -- a sharp increase in slope of Romney Votes - Romney Delegate Votes. Again, anyone looking at this chart that does not think it's worth further investigation either doesn't understand the chart or is trying to derail the discussion.

The charts also explain everything I've been saying about the Romney/Santorum discrepancy. If Romney actually had less candidate votes, that would mean his 'conversion rate' would be much higher, which makes absolute sense based on everything we've been discussing.

That would only be expected if the counties with lower population density should be demographically equivalent to the counties with the highest population density, but why would anyone expect that?

You're trying to make the case that high density areas suddenly vote more for Romney but don't vote for Romney delegates? C'mon.

 

[dsw]

You're trying to make the case that high density areas suddenly vote more for Romney but don't vote for Romney delegates? C'mon.

Nope. See my two questions (in blue) to drummergirl a couple of posts back for what may be a better starting point for where I'm going with that.

I'm also waiting on some clarification from The Man, I hope, about whether my calculations replicated his, or whether I made a mistake. The graph looks roughly right but if I made a mistake on it, even a small one, I want to get that corrected before going deeper into it.

 

[The Man]

Try this DSW. This data is using delegates 2 and 3 averaged, which is what I had in my spreadsheet.

1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
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1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 1
1 2
1 2
1 2
1 2
1 2
1 4
1 4
1 4
1 4
1 4
1 4
1 4
1 4
1 4
1 5
1 5
1 5
1 8
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7 12
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106 23
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114 29
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120 32
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583331 18531

 

[affa]

You're trying to make the case that high density areas suddenly vote more for Romney but don't vote for Romney delegates? C'mon.

Nope. See my two questions (in blue) to drummergirl a couple of posts back for what may be a better starting point for where I'm going with that.

What? Nice try, but no. The only reason you're discussing demographics with Drummergirl is because in your post 534, which was in response to The Man's charts, you brought them up again, even though they're meaningless in regards to The Man's charts.

Heck, you straight up wrote:

And considering that the curve of the Mitt minus dels graph slopes more sharply upward (when suitably smoothed on both the x and y axes) over the same region where the third graph flattens out because from there on out we're drawing >80% of the precincts from the most populous counties, can anyone at least entertain the possibility that there could be a demographic difference at work here? That if your samples are 80% from the most populous counties you might just be looking at some significant demographic differences compared to samples drawn mostly from less populous counties?

... in which you're trying to claim Romney does better against his own delegates because of demographics, which doesn't even begin to make sense. Of course, you don't directly mention this is what The Man's charts are about, because then it would be obvious bringing up demographics made no sense. Instead, you posted some charts and started talking about demographics in a way that implies The Man's charts can be dismissed. Demographics have nothing to do with The Man's charts, and I fail to see why you'd try to obfuscate the conversation by drudging them up in relation to his charts.

And then, in the post I actually quoted, you wrote:

EDIT: more specifically, the rest of that post looks at the way that around the time you get to the "knee" in the graph, you've also gotten to a point at which the remaining data points are 80% from the 20 highest population counties, with just five of those largest counties having twice as much weight from there to the right hand side of the graph than they do overall. What I don't see is why people think the demographics of the precincts represented on the left hand side of the graph should be expected to be close enough to those on the right-hand side of the graph that you can make the inferences that are made. That would only be expected if the counties with lower population density should be demographically equivalent to the counties with the highest population density, but why would anyone expect that?

Again, that sure looks like you're talking about what The Man's charts show, and was in response to The Man, not drummergirl.

And now you're trying to say the demographic discussion is separate from your discussion about The Man's charts? No way. You brought demographics up about them, and more than once, which again, begs the question:

why the heck would any demographic cause people to suddenly start voting for Romney but not his delegates?

 

[The Man]

Quick point- this particular algorithm at 300k that flips to Romney is a small portion of the manipulation. This preliminary chart gives an idea all of the electronic manipulation. This is NOT my final conclusion- there is still much work to be done and new bits to be learned. Note that the X-Axis represents the reference path for all 4 candidate's curves so that all 4 curves ARE the manipulation:

 

[dsw]

Try this DSW. This data is using delegates 2 and 3 averaged, which is what I had in my spreadsheet.

1 0
1 0
1 0
1 0 [...]

Thanks! My results are a bit different, and I'd like to get this exactly right before going deeper, especially because mine isn't showing a knee and that's the region I want to look at more closely.

You start out with a vote total of 1, but I have a handful of precincts with zero votes. One for example is Choctaw county, Halsell precinct:
http://results.enr.clarityelections.com/AL/Choctaw/38325/75721/en/reports.html
I guess only democrats live there. It shows zero votes for GOP candidates, zero in delegate races. I'm guessing you just started the cumulative vote total at 1 rather than 0, to avoid a divide-by-zero somewhere.

But then on line 36 you get (1,1) and I'm still in the zero precincts. (I'm sorting on total votes, then county, then precinct. For me #36 is Wilcox, VOC. BLDG ANNIEMANIE.)

I don't get out of the zeros until line 40 (Choctaw, INTERSECTION). But your cumulative vote total is 1.0 until line 55.

I picked out a few points in the data where the total votes is unique (such as Russell, Roy Martin with 720 total), and we hit these on different lines but at least I can check that my calculation of the average of delegate 2 and delegate 3 is the same as yours, except that you round it to an integer. But I only checked a few that way.

And there seem to be other discrepancies, but if you get a chance to look at the data to see if the above differences indicate anything I'd appreciate it. I'm assuming we're both using the dataset that Liberty posted, right?

 

[The Man]

Thanks! My results are a bit different, and I'd like to get this exactly right before going deeper, especially because mine isn't showing a knee and that's the region I want to look at more closely.

You start out with a vote total of 1, but I have a handful of precincts with zero votes. One for example is Choctaw county, Halsell precinct:
http://results.enr.clarityelections.com/AL/Choctaw/38325/75721/en/reports.html
I guess only democrats live there. It shows zero votes for GOP candidates, zero in delegate races. I'm guessing you just started the cumulative vote total at 1 rather than 0, to avoid a divide-by-zero somewhere.

But then on line 36 you get (1,1) and I'm still in the zero precincts. (I'm sorting on total votes, then county, then precinct. For me #36 is Wilcox, VOC. BLDG ANNIEMANIE.)

I don't get out of the zeros until line 40 (Choctaw, INTERSECTION). But your cumulative vote total is 1.0 until line 55.

I picked out a few points in the data where the total votes is unique (such as Russell, Roy Martin with 720 total), and we hit these on different lines but at least I can check that my calculation of the average of delegate 2 and delegate 3 is the same as yours, except that you round it to an integer. But I only checked a few that way.

And there seem to be other discrepancies, but if you get a chance to look at the data to see if the above differences indicate anything I'd appreciate it. I'm assuming we're both using the dataset that Liberty posted, right?

OK- The "1" vote was inserted to prevent my "cumulative%" calculation from having a "0" in the denominator. That's not going to affect the Y-Axis value at all. It WILL shift the data points to the left by a whopping 1 vote, or 0.000172 % of the width of your chart, or 0.00001375 inches on a 8" wide chart.

I am working from the excel chart that Liberty1789 posted earlier in this thread- will repost the link. So post the graph that you were to create from the data I sent to you.

 

[dsw]

OK- The "1" vote was inserted to prevent my "cumulative%" calculation from having a "0" in the denominator. That's not going to affect the Y-Axis value at all. It WILL shift the data points to the left by a whopping 1 vote, or 0.000172 % of the width of your chart, or 0.00001375 inches on a 8" wide chart.

The difference of 1 isn't a big deal, I was just going through the differences one at a time. Rounding the averages won't make any difference either. But that's not the only difference, as the next few lines of what I wrote illustrated. At line 36 you're apparently hitting a precinct with zero total votes, but your y value goes up so there would have to be some Mitt delegates there, that I don't have. And I hit the first non-zero vote total on line 40, but your cumulative total doesn't go from 1 to 2 until line 55.

These are not significant differences in terms of how the graph looks, but the magnitudes of the differences get larger, and it changes the shape of the graph, so hopefully the first differences encountered will help zero in on where I've got the data wrong. A lot else about the data seems to be in agreement, based on spot checking some of the larger precincts (where I could identify that we were looking at the same precinct even though we hit the precinct at different points because of earlier differences), and where I could find those agreements my calculation of the y value matched yours. So I'm close to being able to replicate the result and dig into it some more, but not quite there yet.

Again: you keep reading this as if you think my using the word "average" or trying to correct a difference of one vote is a critique of what you've done, and it is NOT that in any way; I'm just trying to replicate your result so I can look at it in more depth.

I am working from the excel chart that Liberty1789 posted earlier in this thread- will repost the link.

I was using the link from #94 in this thread, which linked here: http://www.filedropper.com/alabamadelegateraces
But when I go there now it redirects to the front page of that website.
I reloaded my original spreadsheet and verified that in the data I have, there are only 39 precincts with zero total votes, but since your cumulative total doesn't change until line 55 you seem to have more precincts with zero total votes.

Again: not a significant difference in the long run, not a critique, probably my error somewhere, but I can't start digging into the phenomenon until I can replicate the result, and without fixing these early errors the later precincts don't line up and tracking down the discrepancy is much harder.

 

[drummergirl]

Back to your question: Why would "demographics" be at work only in certain places and not others.

That's not a mathematical question, it's an empirical question. And an interesting one, but any time I start responding to the empirical question the (bogus) mathematical argument comes up as a reply. So I'd like to make some progress on the mathematical question first, then come back to he other one.

Two questions:

Do you agree that the marble drawing analogy, and the math that works in that kind of situation, does not apply if the initial sample might be biased in some way? Strictly as a math question.

If we agree on that, then do you agree that the demographics of the more densely-populated counties in a state may reasonably be expected to *possibly* differ demographically from the more sparsely-populated counties in a state? Just as a general question about voter demographics, not about anything else.

Obviously, if you put a "red magnet" in the bottom of the marble bag, the curve shape will be shifted; there will still be 50% red in the end though.

The demographic question is quite important. And a key part of it is that any demographics would have to apply in all similar cases.

Here are 7 demographically similar counties from South Carolina (based on the population density charts from the SC thread). In Oconee County, there is flipping from Paul and Santorum to Romney. In Georgetown there is flipping from Gingrich, Santorum, and Paul to Romney. In Lancaster there is flipping from Gingrich to Romney. In Kershaw and Darlington counties there is no flipping at all.

What demographic factor is there that in very similar circumstances (same election, same day, same state, same size counties, similar vote totals) would cause a positive linear correlation for Romney in 3 cases, but not 2 and would cause inconsistent negative linear correlations for Paul, Gingrich, and Santorum? If demographics explains the slopes, what explains the flat lines?

 

[Joshua2585]

Ron Paul has been winning a tremendous amount of delegates in states that he did not do well in the popular vote? Is this not the same thing, with the coin flipped?

 

[The Man]

Ron Paul has been winning a tremendous amount of delegates in states that he did not do well in the popular vote? Is this not the same thing, with the coin flipped?

Are you seriously comparing the Ron Paul campaign's excellent delegate winning strategy that makes maximum use of all the GOP rules TO criminal electronic vote theft?

 

[dsw]

Obviously, if you put a "red magnet" in the bottom of the marble bag, the curve shape will be shifted; there will still be 50% red in the end though.

The demographic question is quite important. And a key part of it is that any demographics would have to apply in all similar cases.

But the math won't tell you whether the cases are similar are not. Math doesn't have anything to say about whether the 2008 Alabama race (I'd love to get a link to that data if someone turned up more than just the one county) and the 2012 Alabama race are affected by demographic differences in identical ways. With different candidates running, that's not even a reasonable expectation.

I'll give you one example if you wont try to read more into it than I'm saying. The superbrochure people think the SB is super awesome. And they've set up a web site for donations to send them out, and because of the way they set up the web site, saturation in smaller precincts (which are cheaper to "buy") is higher than saturation in larger precincts. Someone posted some very limited data purporting to show that Ron Paul's success in SC correlated with SB saturation. What if they were right, just for the sake of argument? Then because they made it easier to saturate the small precincts, and because saturation correlates with Paul's %vote (they claim), Paul's %vote would tend to decline as precinct size, and SB saturation, go down.

*I'm not making that argument.* Their data (if it holds more widely as they claim) could just as easily be explained because Paul did worse in large precincts due to flipping, and so it's only coincidence that Paul did worse where SB saturation was lower. Or they could be right. They didn't publish enough data to draw any conclusions.

The point I *am* trying to make is that here's one example of an effect that, if genuine, would correlate with precinct size, and apply only in 2012. Romney has also started using a company named TargetPoint to do targeted campaigning, and they brag (without specifics) about doing something radically awesome there about precisely targeted campaigning. Mathematics won't tell you whether or not they're doing something like the inverse of the SB pattern, focusing feet-on-the-ground spending in the precincts that can deliver the most votes, for example. Don't get hung up on those specifics. The point is that Math doesn't predict that there can't be differences between the 2008 and 2012 elections. Math doesn't know what the designers of the superbrochure web site might do in 2012 that they didn't do in 2008, along with countless other potential differences.

My point is that the mathematical argument, the probability calculations, etc., are all only valid if an assumption holds, and it's an assumption that mathematics can't answer. In fact what you've really proven is that the assumption does *not* hold in some cases. So you can't go back and analyze those cases using math that would only be valid if the assumption holds after proving that it does not hold.

Which is not to say that asking *why* there's a difference isn't a valid question. I'm only saying that the mathematical argument is invalid.

Here are 7 demographically similar counties from South Carolina (based on the population density charts from the SC thread). In Oconee County, there is flipping from Paul and Santorum to Romney. In Georgetown there is flipping from Gingrich, Santorum, and Paul to Romney. In Lancaster there is flipping from Gingrich to Romney. In Kershaw and Darlington counties there is no flipping at all.

What demographic factor is there that in very similar circumstances (same election, same day, same state, same size counties, similar vote totals) would cause a positive linear correlation for Romney in 3 cases, but not 2 and would cause inconsistent negative linear correlations for Paul, Gingrich, and Santorum? If demographics explains the slopes, what explains the flat lines?

Are they demographically similar in all respects, or just population density? You talk about "what demographic factor," singular, as if it would have to come down to one. Elections are complex, and how people choose between one candidate and another is complex. And to even start to look at this you'd have to look at what correlates with precinct size in those different counties. Is there geographical clustering, as in Va Beach City? If so, do the larger precincts tend to come from more affluent areas?

In fact, let's just look. I just went to zillow, looked at Va Beach City, set a min price of 1 million, and what do you know? That large cluster in the northeast, the one that constituted 60% of the data to the right of the "crime" point, also turns out to be a cluster of the most expensive houses. So the big jump in the graph is *exactly* at the first precinct you hit of several that are all apparently in one of the most affluent areas. A neighborhood that is affluent and (if the data is genuine) very pro-Romney. This happened because the precinct size order results in a strong pattern of geographical clustering, and more than half of the largest precincts are in a geographical cluster that also happens to be very affluent. (And that wasn't the only cluster to the right of the "crime" point.)

Nothing in math tells you that these kinds of correlations won't happen. And notice that this wasn't a simple one. The geographical clustering alone is suggestive, but doesn't explain the graph. The affluence of certain areas, with affluent areas skewing pro-Romney, wouldn't be enough to explain the graph. It took the combination of those factors, so that you hit (exactly at the "crime" point) the first of several very affluent and very pro-Romney precincts that, because the sorted order results in geographical clustering, all end up bunched together in the last precincts on the graph.

 

[dsw]

Ron Paul has been winning a tremendous amount of delegates in states that he did not do well in the popular vote? Is this not the same thing, with the coin flipped?

Other people have asked that, but it's a misunderstanding of how things were done in Alabama. Some states had a straw poll or whatever, and a separate thing entirely for selecting delegates, and Paul in some cases did very, very well in the latter and not so well in the former.

In Alabama, it's one ballot for both. But also, the delegate races aren't choosing between delegates for different candidates. Each delegate race is for people who want to be a delegate for one candidate. It's choosing who would be the potential first delegate for Ron Paul, for example, between two Ron Paul supporters. So Paul's strategy for winning delegates that has been so effective elsewhere doesn't really apply in Alabama.

 

[The Man]

I need some feedback from any of you on a method of "adjusting" delegates for the purpose of eliminating noise. Some basic facts:

1. Delegate votes, regardless of position number, are believed to be proportionally representative of the cast votes in the Alabama 2012 Primary.
2. None of the delegate votes position final totals exactly matches the candidate vote final totals.

Because the delegate votes totals of just about every precinct deviate erratically, I have devised a simple "adjustment" that largely eliminates erratic noise in each candidate's "votes minus delegates" calculation" that I have appplied in each precinct:

#Delegates each candidate for a particular precinct (Adjusted) = [(reported votes total all candidates for precinct) / (total delegates all candidates for precinct)] X candidate's reported delegates for particular precinct.

In other words, we are simply adjusting the number each candidate's delegates in each precinct according using the ratio of (total votes reported) / (total delegates reported).

The results are pretty dramatic, especially for Paul and Gingrich:

Question: Why does the adjustment appear to dramatically reduce noise for all candidates EXCEPT Santorum? I have no idea.