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06 Feb 23:36

Donald Trump Had A Superior Electoral College Strategy

by Nate Silver

This is the sixth article in a series that reviews news coverage of the 2016 general election, explores how Donald Trump won and why his chances were underrated by the most of the American media.

By one measure, Wisconsin was the most important state in the nation in November. According to FiveThirtyEight’s tipping-point calculation, it was the state that put Donald Trump over the top to 270 electoral votes and the White House. (Or at least arguably it did: Pennsylvania has a competing tipping-point claim.) So here’s an interesting question: How many times did Hillary Clinton visit Wisconsin during the general election? The answer: Zip, zilch, nada. She didn’t set foot in the Badger State after losing the Democratic primary there to Sen. Bernie Sanders in April.

So, case closed, right? Clinton had an incompetent Electoral College strategy and maybe even blew the election because of it? Well, yes and no. She probably should have campaigned in a broader range of states. In particular, she should have spent more time in states, such as Wisconsin, where she was narrowly leading in polls but that had the potential to flip to Trump if the election tightened, as it did during the final 10 days of the campaign.

This very probably didn’t cost Clinton the election, however — and the importance of Electoral College tactics is probably overstated in general. I’m going to save that discussion for the next article in this series, but in the meantime … I come in praise of Trump’s Electoral College approach and in criticism of Clinton’s. Indeed, Trump was pretty close to having an optimal Electoral College strategy as judged by our tipping-point calculation. Clinton made a couple of mistakes, meanwhile. So did campaign reporters, who usually lauded Clinton’s strategy while maligning Trump’s, making essentially the same errors that the Clinton campaign did.

Which states did the candidates consider to be most important? Perhaps the best gauge is simply where Clinton and Trump spent their time. Clinton’s campaign (less so Trump’s) had enormous resources to spend on television advertising, enough that she probably encountered diminishing returns among swing-state voters who had seen as many of her commercials as they could stand. Candidate visits, however, are the ultimate scarce resource. No matter how much money or how many staffers you have, you’ll only have one Hillary Clinton or Donald Trump.

Here, then, is how the candidates distributed their time from Sept. 1 through the day before the election, based on the share of their public events that occurred in each state. (Note that Trump overall was a considerably more active campaigner than Clinton, holding 105 events to her 70 during this period.) For comparison, I’ve listed how likely each state was to be the tipping-point state, based on how it ranked on average from Sept. 1 to Nov. 7, according to our polls-only model.

Florida 17.4% 20.0% 18.1%
Pennsylvania 11.5 11.4 11.4
Michigan 9.0 4.3 5.7
North Carolina 8.6 14.3 11.4
Ohio 8.2 11.4 9.5
Colorado 6.1 1.4 7.6
Wisconsin 6.1 0.0 2.9
Virginia 5.7 0.0 3.8
Minnesota 4.5 0.0 1.0
Nevada 3.2 4.3 4.8
New Hampshire 2.5 4.3 6.7
Arizona 2.5 1.4 1.9
Georgia 2.0 0.0 0.0
Iowa 1.9 4.3 2.9
New Mexico 1.5 0.0 1.0
Trump probably had a better tipping-point strategy than Clinton

Tipping-point probabilities based on FiveThirtyEight’s polls-only model

Sources: Conservative Daily News,

One thing to notice is that Clinton and Trump’s strategies are not all that different. Clinton has been criticized for not spending enough time in Michigan, for instance, but on a percentage basis, she spent only slightly less time there than Trump did.

Still, Trump’s strategy was closer to the one we would have recommended. There were two major errors, from our standpoint, in Clinton’s approach.

Error no. 1: Clinton focused too much on close states rather than tipping-point states. On average from Sept. 1 through Nov. 7, the closest states in our polls-only model were Ohio, Nevada, North Carolina, Iowa and Florida. And yet Clinton spent more time in these states than she should have. A combined 54 percent of Clinton’s events (and 47 percent of Trump’s) were held in these states, whereas there was only a 39 percent chance that one of them would be the tipping-point state.

How can it have been a mistake for Clinton to focus on these states when they were so close? In a nutshell, they weren’t “must win” states for her. On average during this period, Clinton was projected to win roughly 310 electoral votes. A slightly Republican-leaning state such as Ohio might easily have given Clinton her 300th or 320th electoral vote in the event of a clear win nationally. But others, like Pennsylvania, were more likely to provide the decisive 270th electoral vote, and that’s what the tipping-point calculation measures.

A good rule of thumb is that tipping-point states are those polling closest to the national average. Before FBI Director James Comey’s letter to Congress, for instance, Clinton’s lead in Michigan had been roughly 6 percentage points. She was up by about the same amount in Wisconsin and Pennsylvania. But she was leading nationally by about 6 points, also. Therefore, states like Michigan were actually good ones for Trump and Clinton to campaign in, on the prospect that they’d become competitive if the race tightened, as it did — better than states like Ohio or Iowa, which were closer at that moment but further from the tipping point.

It’s also the case that the best defense is sometimes a good offense. Florida and North Carolina might not have been must-win states for Clinton, but they potentially were must-wins for Trump. So it wasn’t a bad idea for her to be spending some time in them. In general, however, the correct strategy for a candidate with an overall Electoral College lead can be surprisingly conservative, involving spending time and money in states that seem fairly safe but that could slip in the event of a shift in the race or systematic polling error. In Clinton’s case, that would have included more time in states such as Michigan, Wisconsin and Colorado.

Error no. 2: Clinton was overconfident and campaigned in too narrow a range of states. Clinton played a considerably narrower map than Trump did. In addition to Wisconsin, she also skipped Virginia, Minnesota and New Mexico during the closing stages of the campaign; Trump visited all of those states. And she spent much less time than he did in Colorado.

Apart from Wisconsin, Trump didn’t win any of these states (although he came close in Minnesota). But he had more or less the right strategy given the overall uncertainty in the race. The point is not that candidates are supposed to be clairvoyant — that it should have been obvious to Trump and Clinton that they needed to campaign in Wisconsin but didn’t have to worry about Colorado, for instance. In an alternate reality, college-educated suburbanites — instead of whites without college degrees — might have shifted toward Trump late in the race, narrowly putting him over the top in Colorado. It’s precisely because the polls can be wrong in ways that you don’t anticipate — and because news events can shift them in unpredictable ways — that you want to play a fairly broad map.

Why did the supposedly data-savvy Clinton campaign make these mistakes? Perhaps because they’re easy mistakes to make. I’m sure that it had highly sophisticated forecasts and models of the campaign and has a rigorous understanding of concepts such as tipping-point states. But for both technical and nontechnical reasons, it’s much easier to build an overconfident model than an underconfident one. This can especially be the case when you rely on proprietary data, such as internal polls. As I’ll describe in a future article in this series, it’s not clear that internal polls are better than public polling averages. If campaigns wrongly believe that they’ve solved the riddle of polling, they might make overconfident decisions, going “all in” on certain strategies instead of diversifying their approach.

Furthermore, decisions about where to spend time and money aren’t made in a vacuum. Like any other kind of organization, campaigns are subject to internal politics and potentially misaligned incentives, and their decisions can be influenced by outside groups, such as donors and the media. Making the technically correct decision may not be easy if it contradicts the conventional wisdom, and correct Electoral College strategy (i.e., not necessarily campaigning in the closest states if they aren’t near the tipping point) is often slightly counterintuitive.

Speaking of the conventional wisdom, we should talk some about how the media covered Clinton’s and Trump’s Electoral College tactics. Being among the most technical aspects of the campaign, this was generally not a strength of mainstream coverage. For instance, on Oct. 30, The New York Times jabbed at Trump for “campaigning well outside the traditional band of states that decide presidential elections,” including in New Mexico and Michigan, “two solidly blue states where polling has shown Mrs. Clinton with a clear lead” — failing to recognize that they were potentially tipping-point states even if Clinton was ahead there. A few days later, on Nov. 3, the Times criticized Trump for campaigning in too wide a range of states:

Rather than wielding data and turnout machinery as tools, Mr. Trump has instead battered at the political map in a less discriminating way, trying to shift the national race a point or two in his favor and perhaps find a soft spot in Mrs. Clinton’s support.

This was, it would turn out, pretty much exactly the strategy that swung the Electoral College to Trump. The national race tightened by a percentage point or two — actually a bit more than that after Comey’s letter to Congress — and Trump found a soft spot in Clinton’s support in Wisconsin, Michigan and Pennsylvania. As you read appraisals that second-guess Clinton campaign’s tactics, keep in mind that reporters often had the same blind spots. Trump was also often scolded by pundits and analysts for campaigning in the very states that would win him the presidency.

To some extent, the media’s misconceptions about Electoral College strategy and Clinton’s errors may have reinforced one another. For the most part, decisions about where to allocate resources should be determined by where states line up relative to one another. Typically, news events produce similar changes in lots of states at once, so even a major shock (say, Comey’s letter or the release of Trump’s “Access Hollywood” tape) won’t change the correct Electoral College approach all that much. The chart below provides some examples of how states’ tipping-point probabilities were fairly steady, even with all the ups and downs of the campaign.


Despite this, the media tended to read these tactical decisions as revealing a candidate’s absolute strength, rather than the relative importance of the states. A foray into traditionally Republican Arizona, for instance, would be read as a sign of strength for Clinton while a trip to traditionally blue Wisconsin would be seen as an admission of weakness. If a candidate was too concerned about her media clippings, that could inhibit correct decision-making. One wonders whether the reason Clinton never totally abandoned Iowa, for instance — even though she rarely polled well there and it was highly unlikely to be the tipping-point state — is because doing so would have occasioned a media freakout.

Conversely, Trump’s data team wasn’t likely to get a lot of credit from the media almost no matter what it did. With rare exception, reporters tended to portray Trump’s Electoral College strategy as being whimsical and haphazard, even when it was doing some pretty smart things. That may have helped Trump’s team to shut out the noise and maximize its candidate’s chances of winning the election.

14 Apr 15:36

Draft of Anti-Encryption Bill Officially Released

29 Dec 18:54

Using the new Apple TV to emulate classic game consoles

by Andrew Cunningham

Enlarge / The Apple TV and the Horipad Ultimate MFI controller. (credit: Andrew Cunningham)

For those of us fortunate enough to have the privilege, late December and early January bring two things: new toys and a bit of vacation time. That makes it a great time to tinker with little tech projects, things that are inessential and maybe a bit time-consuming but fun enough and useful enough to be worth doing.

One of my projects was to experiment with classic console emulators on the new Apple TV. There aren’t many of them yet, and installation takes a little work (Apple doesn’t allow add-your-own-ROM emulators in the App Store), but new capabilities introduced in iOS 9 and the iOS-based tvOS make it possible to install them.

Emulation and the Apple TVx

Right now there are two notable emulation projects targeting tvOS. One is a distant relative of the MAME arcade emulator, though it doesn’t seem as though it’s being maintained. Another, Provenance, is the one we’ll be spending the most time with. It’s a multi-system emulator that supports most major 8- and 16-bit consoles, including the NES, SNES, Sega Master System, Sega Genesis, Sega CD, Game Boy, and Game Boy Advance.

Read 17 remaining paragraphs | Comments

14 May 06:37

The last male northern white rhino

13 May 07:08

The Software Behind Frank Gehry’s Geometrically Complex Architecture

05 May 23:27

Phind Is Shazam For Location — Snap A Photo, Pull In All The Info, Book Stuff

by Mike Butcher
phind11 You find yourself traveling abroad or in a strange city and need to work out where you are and what’s around you. What do we all do? It’s a familiar process. You take out your smartphone and open multiple apps: Foursquare, Yelp, Maps, Wikipedia, Trip Advisor, etc. The list goes on. After perusing multiple channels of information, you’ve basically lost plenty of time at… Read More
23 Mar 05:13

Uber Takes Strategic Investment From Times Internet To Boost Its Visibility In India

by Jon Russell
uber headquarters India is Uber’s second largest market worldwide behind only the U.S., and the company is today bolstering its position in the Asian country after agreeing to an alliance with media firm Times Internet. One component of that deal is an undisclosed investment from Times Internet. Read More
08 Feb 07:26

Clash of Clans upgrade scheduling problem.

I don't know if any readers play this game, but it's not important. I want to find an algorithm to solve the following problem.

There are several buildings, and each of them have a list of upgrades, the upgrades have to be done in order (these are just simple checking, I can do). The upgrades are measured in days.

I have n builders, for convenience n is from 1~5.

Now I want to schedule the upgrades to the n builders, but here's the trick, I want to have at least a builder finish a build every single day, the reason is not important.

So the following is a valid schedule:

Builder 1: Archer Tower 3 days, Cannon 1 day

Builder 2: Cannon 1 day, Cannon 1 day, Barracks 3 days

Because Builder 1 is free on day 3, 4 and 5, and Builder 2 is free on day 1, 2, 5.

But following is not valid:

Builder 1: Archer Tower 3 days, Cannon 1

Builder 2: Barracks 3 days, Cannon 1, Cannon 1

Because there are no builders free on day 1 and 2.

So is it possible to solve this in reasonable time? Cause I wrote a program to try all combos and it cannot finish in reasonable time.

I'm a second year university student, so my knowledge in this field is still not that much.

Thank you for reading, and thank you for helping out.

submitted by cheeseonhead
[link] [2 comments]
11 Oct 20:16

Flight Attendants: The New Personal Electronics Rules Suck

by Chris Mills

Flight Attendants: The New Personal Electronics Rules Suck

The rest of us might be celebrating that we can finally keep playing Candy Crush during takeoff or landing , but flight attendants don't seem to be too happy about the new regulations: the biggest union for flight attendants is suing the FAA to change the rules back.


03 Aug 04:37

100,000 DOM Updates

29 Jul 04:47

Monday puzzle: choosing randomly with a coin

by Presh Talwalkar

A group of 3 friends cannot agree on where to eat. Each person prefers a different restaurant and no one is willing to compromise.

Eventually they agree it would be fair to choose the restaurant at random. How can they use a coin to decide, making sure each restaurant is picked with equal chance?

What if the coin is biased, but they don’t know if it produces more heads or tails?

Extension: how can you use a coin to choose between n items equally? What if the coin is biased?

Answer to choosing randomly with a coin

If the coin is fair, there is a simple procedure for choosing between 3 items randomly. The group can flip the coin two times, and that will produce 4 events with equal probability: HH, HT, TH, and TT. Let the first three outcomes correspond to each of the three choices. If the fourth event happens (TT), then disregard it and repeat with two more flips.

In other words, flip the coin two times and then let:

HH: choice 1
HT: choice 2
TH: choice 3
TT: do-over, flip the coin 2 more times and repeat

There will be some do-overs, but mostly this procedure will result in a choice in a matter of a few tries.

As an aside, if we relabel the choices as 0, 1, 2, we can “encode” the coin flips as binary bits for a natural mapping between the flips and the choices. If we let H = 0 and T = 1, then

HH = 00 = choice 0
HT = 01 = choice 1
TH = 10 = choice 2
HH = 11 –> repeat

What if the coin is biased?

If heads occurs more frequently than tails, it will no longer be true that HH and HT occur with the same probability. So how can we choose between 3 items in this case?

It seems like we are stuck, but we can use a trick. Let’s first see how we can choose between 2 items. In other words, let’s make a “fair toss” from this unfair coin.

The procedure is this. Flip the coin 2 times. Let HT denote one choice and TH denote the other. If the flip is HH or TT, then disregard and repeat with two flips again.

We can prove this results in creating two events that happen with equal chance. To see why, let’s say that H occurs with probability p and T with probability 1 – p. When we flip the coin twice, we have:

HT occurs with p(1 – p)
TH occurs with (1 – p)p

We’ve created two events that happen with equal chance, even though the coin itself is biased. The trick was making sure to only consider outcomes where the number of H’s equals the number of T’s.

How can we generalize this for choosing between 3 items?

What we have to do is flip the coin 4 times. Now we disregard the ouctcome if the number of H’s and T’s is not equal. We are left with 6 choices in which there are 2 H’s and 2 T’s. We can label these as follows:

HHTT, HTHT: choice 1
HTTH, THHT: choice 2
THTH, TTHH: choice 3
any other result: disregard and repeat the 4 tosses again

This procedure will result in each of the three restaurants being chosen with equal chance.

(Obviously this is just one way to label the outcomes with choices. Any method that assigns 2 of the equally likely events to each of the 3 choices will be valid.)

Generalizing to n

Based on this logic we can make random choices between n choices using a coin. (This is not the most efficient way to do it, but it’s easy to understand which is important so everyone can agree the procedure is fair!)

If the coin is fair: flip the coin k times with 2k ≥ n > 2k-1. Label n of the equally outcomes with each of the choices 1, 2, …, n. For any other outcome flip the coin again until it results in one of the labeled choices.

If the coin is not fair: We need to flip the coin so there are at least n outcomes where the number of heads is equal to the number of tails. That means we should flip the coin 2k times such that 2k choose k ≥ n. Label n of the equally outcomes with each of the choices 1, 2, …, n. (We can make this slightly more efficient. We can actually accept jn of the outcomes by dividing the outcomes into n groups of j outcomes each. Recall that in the case of n = 3, we has 6= 2*3 outcomes that were divided into 3 groups where each choice got 2 outcomes). For any other outcome flip the coin again until it results in one of the labeled choices.

10 Jul 03:54

Startup Investing Trends

05 Jul 18:58

STABiLGO Kickstarter Hopes To Take Its Action Sport Video Stabilizer To Market

by Eliza Brooke

Watching GoPro footage makes it clear that there is basically nothing cooler than first-person action sport shots. And for those who are spending the day at the skate park, one Kickstarter project is hoping to take that genre of filming to the next level.

STABiLGO is a handheld, motorized GoPro stabilizer that keeps the camera level and steady as you turn down a half-pipe or mountain. Creators Michael Boczon and Christine Reilly have raised $33,885 of their $100K goal so far with 12 days left.

If you’re wondering how this product didn’t exist already — produced by someone like GoPro or one of its die-hard fans, for instance — don’t ask Boczon. He doesn’t know either. A technical producer and video editor at MTV, he said others had advanced directly to creating aerial rigs and somehow bypassed handheld stabilizers. But Boczon and Reilly have clearly caught a technology wave that others are riding, too. The day after they had been rewinding motors for the STABiLGO, a pre-made motor became available for purchase online.

After playing catch-up with the development of the individual components, STABiLGO seems to have broken ahead of the pack. After STABiLGO went up on Kickstarter, six different groups reached out to say that Boczon had beaten them to the punch by only a few weeks.

The aim is to move STABiLGO into retail production in China, which Boczon said he intends to do with or without the Kickstarter money. The prototype costs about $450 in parts to produce, and Boczon said they would likely set the retail price between $600-$700.

“In the end, our goal was to use it when we go snowboarding,” he said. “Come this season, I will have my unit.”