Election Poll Error
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Tank - Our Lives in Numbers September 8, 2016 5 key things to know about the margin of error in election polls By Andrew Mercer8 comments In presidential elections, even the smallest changes in horse-race poll results seem survey margin of error calculator to become imbued with deep meaning. But they are often overstated. Pollsters disclose
Presidential Poll Margin Of Error
a margin of error so that consumers can have an understanding of how much precision they can reasonably expect. But margin of error in polls cool-headed reporting on polls is harder than it looks, because some of the better-known statistical rules of thumb that a smart consumer might think apply are more nuanced than they seem. In other
Margin Of Error Formula
words, as is so often true in life, it’s complicated. Here are some tips on how to think about a poll’s margin of error and what it means for the different kinds of things we often try to learn from survey data. 1What is the margin of error anyway? Because surveys only talk to a sample of the population, we know that the result probably won’t exactly polls with margin of error and sample size match the “true” result that we would get if we interviewed everyone in the population. The margin of sampling error describes how close we can reasonably expect a survey result to fall relative to the true population value. A margin of error of plus or minus 3 percentage points at the 95% confidence level means that if we fielded the same survey 100 times, we would expect the result to be within 3 percentage points of the true population value 95 of those times. The margin of error that pollsters customarily report describes the amount of variability we can expect around an individual candidate’s level of support. For example, in the accompanying graphic, a hypothetical Poll A shows the Republican candidate with 48% support. A plus or minus 3 percentage point margin of error would mean that 48% Republican support is within the range of what we would expect if the true level of support in the full population lies somewhere 3 points in either direction – i.e., between 45% and 51%. 2How do I know if a candidate’s lead is ‘outside the margin of error’? News reports about polling will often say that a candidate’s lead is
his electoral defeat. This image has become iconic of the consequences of bad polling data. An opinion poll, sometimes simply referred to as a poll, is a human research survey
What Is A Good Margin Of Error
of public opinion from a particular sample. Opinion polls are usually designed to represent
Margin Of Error Definition
the opinions of a population by conducting a series of questions and then extrapolating generalities in ratio or within confidence acceptable margin of error intervals. Contents 1 History 2 Sample and polling methods 2.1 Benchmark polls 2.2 Brushfire polls 2.3 Tracking polls 3 Potential for inaccuracy 3.1 Nonresponse bias 3.2 Response bias 3.3 Wording of questions 3.4 Coverage http://www.pewresearch.org/fact-tank/2016/09/08/understanding-the-margin-of-error-in-election-polls/ bias 4 Failures 5 Social media as a source of opinion on candidates 6 Influence 6.1 Effect on voters 6.2 Effect on politicians 7 Regulation 8 See also 9 Footnotes 10 References 10.1 Additional Sources 11 External links History[edit] The first known example of an opinion poll was a local straw poll conducted by The Aru Pennsylvanian in 1824, showing Andrew Jackson leading John Quincy Adams by https://en.wikipedia.org/wiki/Opinion_poll 335 votes to 169 in the contest for the United States Presidency. Since Jackson won the popular vote in that state and the whole country, such straw votes gradually became more popular, but they remained local, usually city-wide phenomena. In 1916, the Literary Digest embarked on a national survey (partly as a circulation-raising exercise) and correctly predicted Woodrow Wilson's election as president. Mailing out millions of postcards and simply counting the returns, the Digest correctly predicted the victories of Warren Harding in 1920, Calvin Coolidge in 1924, Herbert Hoover in 1928, and Franklin Roosevelt in 1932. Support For Direct Popular Vote in the United States Then, in 1936, its 2.3 million "voters" constituted a huge sample; however, they were generally more affluent Americans who tended to have Republican sympathies. The Literary Digest was ignorant of this new bias. The week before election day, it reported that Alf Landon was far more popular than Roosevelt. At the same time, George Gallup conducted a far smaller, but more scientifically based survey, in which he polled a demographically representative sample. Gallup correctly predicted Roosevelt's landslide victory. The Literary Digest soon went out of business, while polling started to take off. Elmo Roper was anot
and economic issues such as unemployment and government spending were the dominant themes of the campaign. The Literary Digest was one of the most respected magazines of the time and had a history of accurately predicting the winners of presidential elections that https://www.math.upenn.edu/~deturck/m170/wk4/lecture/case1.html dated back to 1916. For the 1936 election, the Literary Digest prediction was that Landon would get 57% of the vote against Roosevelt's 43% (these are the statistics that the poll measured). The actual results of the election were 62% for Roosevelt against 38% for Landon (these were the parameters the poll was trying to measure). The sampling error in the Literary Digest poll was a whopping 19%, the largest ever in a major public opinion poll. Practically margin of all of the sampling error was the result of sample bias. The irony of the situation was that the Literary Digest poll was also one of the largest and most expensive polls ever conducted, with a sample size of around 2.4 million people! At the same time the Literary Digest was making its fateful mistake, George Gallup was able to predict a victory for Roosevelt using a much smaller sample of about 50,000 people. This illustrates the fact that margin of error bad sampling methods cannot be cured by increasing the size of the sample, which in fact just compounds the mistakes. The critical issue in sampling is not sample size but how best to reduce sample bias. There are many different ways that bias can creep into the sample selection process. Two of the most common occurred in the case of the Literary Digest poll. The Literary Digest's method for choosing its sample was as follows: Based on every telephone directory in the United States, lists of magazine subscribers, rosters of clubs and associations, and other sources, a mailing list of about 10 million names was created. Every name on this lest was mailed a mock ballot and asked to return the marked ballot to the magazine. One cannot help but be impressed by the sheer ambition of such a project. Nor is is surprising that the magazine's optimism and confidence were in direct proportion to the magnitude of its effort. In its August 22, 1936 issue, the Litereary Digest announced: Once again, [we are] asking more than ten million voters -- one out of four, representing every county in the United States -- to settle November's election in October. Next week, the first answers from these ten million will begin the incoming tide of marked ballots, to be triple-checked, verified, five-times cross-classified and totaled. When the last figure has been totted and checked, if pa