The collected data will quantify how fatigue from training, competing, travel, time-zone adjustments and other variables affect multiple aspects of game-day performance such as reaction time and readiness.
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. InRasmussen Reports had an apparently short-term partnership with FiveThirtyEight in order to include this unique methodology for generating poll averages in their "Balance of Power Calculator".
Much like Grantlandwhich ESPN launched inthe 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 It's a data journalism site. Politics is one topic that sometimes data journalism is good at covering. It's certainly good with presidential elections.
But we don't best science writers 2013 nba see politics as how the site is going to grow". The lead story by Silver explained that "FiveThirtyEight is a data journalism organization We've expanded our staff from two full-time journalists to 20 and counting. 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. So in addition to written stories, we'll have interactive graphics and features".
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 Indianafor 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 Julythe 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 Nebraskawhich 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.Breaking news and analysis from timberdesignmag.com Politics, world news, photos, video, tech reviews, health, science and entertainment news.
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