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As Mark Blumenthal wrote in National Journal , "Over the last week, an anonymous blogger who writes under the pseudonym Poblano did something bold on his blog, FiveThirtyEight. He posted predictions for the upcoming primaries based not on polling data, but on a statistical model driven mostly by demographic and past vote data Most of the public polls pointed to a close race in North Carolina But a funny thing happened. The model got it right". This model, too, relied in part on demographic information but mainly involved a complex method of aggregating polling results. Much like Grantland , which ESPN launched in , the site will retain an independent brand sensibility and editorial point-of-view, while interfacing with other websites in the ESPN and Disney families. The site will return to its original URL, www. But we take our science and economics and lifestyle coverage very seriously Politics is one topic that sometimes data journalism is good at covering. Our team also has a broad set of skills and experience in methods that fall under the rubric of data journalism. These include statistical analysis, but also data visualization, computer programming and data-literate reporting. At base Silver's method is similar to other analysts' approaches to taking advantage of the multiple polls that are conducted within each state: But especially in the early months of the election season polling in many states is sparse and episodic. The "average" of polls over an extended period perhaps several weeks would not reveal the true state of voter preferences at the present time, nor provide an accurate forecast of the future. One approach to this problem was followed by Pollster. However, while adopting such an approach in his own analysis, Silver reasoned that there was additional information available in polls from "similar" states that might help to fill the gaps in information about the trends in a given state. Accordingly, he adapted an approach that he had previously used in his baseball forecasting: He carried this approach one step further by also factoring national polling trends into the estimates for a given state. Thus, his projections were not simply based on the polling trends in a given state. Furthermore, a basic intuition that Silver drew from his analysis of the Democratic party primary elections was that the voting history of a state or Congressional district provided clues to current voting. This is what allowed him to beat all the pollsters in his forecasts in the Democratic primaries in North Carolina and Indiana , for example. For his general election projections for each state, in addition to relying on the available polls in a given state and "similar states," Silver estimated a " regression " using historical voting information along with demographic characteristics of the states to create an estimate that he treated as a separate poll equivalent to the actually available polls from that state. This approach helped to stabilize his projections, because if there were few if any polls in a given state, the state forecast was largely determined by the regression estimate. In July , the site began to report regular updates of projections of U. Special procedures were developed relying on both polls and demographic analysis. The projections were updated on a weekly basis. Silver's predictions matched the actual results everywhere except in Indiana and the 2nd congressional district of Nebraska , which awards an electoral vote separately from the rest of the state. His projected national popular vote differential was below the actual figure of 7. The forecasts for the Senate proved to be correct for every race. But the near stalemate in Minnesota led to a recount that was settled only on June 30, In Alaska , after a protracted counting of ballots, on November 19 Republican incumbent Ted Stevens conceded the seat to Democrat Mark Begich , an outcome that Silver had forecast on election day. After the U. A substantial percentage of the articles focused on Senatorial races: During the post election period Silver devoted attention to developing some tools for the analysis of forthcoming Congressional elections , [ 13] [ 14] as well as discussing policy issues and the policy agenda for the Obama administration, especially economic policies. According to Silver's analysis, Strategic Vision's data displayed statistical anomalies that were inconsistent with random polling. Later, he uncovered indirect evidence that Strategic Vision may have gone as far as to fabricate the results of a citizenship survey taken by Oklahoma high school students, which led him to denounce Strategic Vision as "disreputable and fraudulent. International affairs columnist Renard Sexton began the series with an analysis of polling leading up to the election; [ 23] then posts by Silver, Andrew Gelman and Sexton analyzed the reported returns and political implications. The " model" once again aggregated the disparate polls to correctly predict that the Republican Scott Brown would win. The majority of polling organisations in the UK use the concept of uniform swing to predict the outcome of elections. However, by applying his own methodology, Silver produced very different results, which suggested that a Conservative victory might have been the most likely outcome. Silver expanded the database to more than 4, election polls and developed a model for rating the polls that was more sophisticated than his original rankings. Well, it's here [citing his June 6 article], in an article that contains 4, words and 18 footnotes. Every detail of how the pollster ratings are calculated is explained. It's also here [referring to another article], in the form of Pollster Scorecards, a feature which we'll continue to roll out over the coming weeks for each of the major polling firms, and which will explain in some detail how we arrive at the particular rating that we did for each one". The polling database was compiled from approximately eight or ten distinct data sources, which were disclosed in a comment which I posted shortly after the pollster ratings were released, and which are detailed again at the end of this article. These include some subscription services, and others from websites that are direct competitors of this one. Although polls contained in these databases are ultimately a matter of the public record and clearly we feel as though we have every right to use them for research purposes, I don't know what rights we might have to re-publish their data in full". Silver also commented on the fact that the ratings had contributed to Markos Moulitsas 's decision to end Daily Kos 's use of Research as its pollster. Other researchers questioned aspects of the methodology. Presidential primaries and general elections, state governor elections, and U. Congress elections for the years — The blog would be listed under the "Politics" tab of the News section of the Times. Silver received bids from several major media entities before selecting the Times. You shouldn't want to belong to any media brand that seems desperate to have you as a member, even though they'll probably offer the most cash". At the same time, Silver published a brief history of the blog. Senate , the U. House of Representatives , and state Governorships. Each of these models relied initially on a combination of electoral history, demographics, and polling. The model had forecast a net pickup of 8 seats by the Republicans in the Senate and 55 seats in the House, close to the actual outcome of a pickup of 6 seats in the Senate and 63 seats in the House. Silver, Renard Sexton and Hale Stewart. Andrew Gelman contributed again in early Cohen provided a periodic "Reads and Reactions" column in which he summarized Silver's articles for the previous couple of weeks, as well as reactions to them in the media and other blogs, and suggested some additional readings related to the subject of Silver's columns. Silver identified Cohen as "my news assistant". Enten and identified him as the "whiz kid" of FiveThirtyEight and an example of a new generation of political journalists who are very analytical and data-based. Silver pointed out that conflicts with the police caused the sharpest increases in news coverage of the protests. The model forecasts both the popular vote and the electoral college vote, with the latter being central to the exercise and involving a forecast of the electoral outcome in each state. In the initial forecast, Barack Obama was estimated to have a The website provided maps and statistics about the electoral outcomes in each state as well as nationally. Later posts addressed methodological issues such as the "house effects" of different pollsters as well as the validity of telephone surveys that did not call cell phones. On election day, November 6, Silver posted his final forecast for each state. On the morning of the November 6, presidential election, Silver's model gave President Barack Obama a For example, Rasmussen Reports "missed on six of its nine swing-state polls". And assuming that his projected margin of error figures represent 95 percent confidence intervals, which it is likely they did, Silver performed just about exactly as well as he would expect to over 50 trials. As of July, it had a staff of 20 writers, editors, data visualization specialists, and others. In addition to feature articles it produced podcasts on a range of subjects. Monthly traffic to the site grew steadily from about 2. Senate elections being contested that year. However, FiveThirtyEight editor Nate Silver also remarked, "An equally important theme is the high degree of uncertainty around that outcome. A large number of states remain competitive, and Democrats could easily retain the Senate". The polls-only model relied only on polls from a particular state, while the polls-plus model was based on state polls, national polls and endorsements. For each contest, FiveThirtyEight produced probability distributions and average expected vote shares per both of these models. He argued that by giving "Mr. Trump a 2 percent chance at the nomination despite strong polls in his favor Silver wrote, "The big mistake is a curious one for a website that focuses on statistics. Instead, they were what we [call] 'subjective odds' — which is to say, educated guesses. In other words, we were basically acting like pundits, but attaching numbers to our estimates. And we succumbed to some of the same biases that pundits often suffer, such as not changing our minds quickly enough in the face of new evidence. Without a model as a fortification, we found ourselves rambling around the countryside like all the other pundit-barbarians, randomly setting fire to things". Bernie Sanders could "lose everywhere else after Iowa and New Hampshire"  and that the "Democratic establishment would rush in to squash" him if he does not. The core data employed were polls, which FiveThirtyEight aggregated for each state while also considering national polls using essentially the same method it had employed since In the primaries, the projections also took into account endorsements. FiveThirtyEight projected a much higher probability of Donald Trump winning the presidency than other pollsters,  a projection which was criticized by Ryan Grim of the Huffington Post as "unskewing" too much in favor of Trump. According to the Foundation, "In his posts, former economic analyst and baseball-stats wunderkind Nate Silver explains the presidential race, using the dramatic tension inherent in the run-up to Election Day to drive his narrative. Come November 5, we will have a winner and a loser, but in the meantime, Silver spins his story from the myriad polls that confound us lesser mortals". The Magazine for Students of Statistics. FiveThirtyEight was named the "Data Journalism Website of the Year" for by the Global Editors Network , a Paris-based organization that promotes innovation in newsrooms around the world. The award summary stated: Congressional boundaries can make or break political careers and shape the direction of national lawmaking for a decade.
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