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Photo shows Harry S. Truman displaying a newspaper whose headline states “Dewey Defeats Truman.”
Polling process errors can lead to incorrect predictions. On November 3, the day after the 1948 presidential election, a jubilant Harry S. Truman triumphantly displays the inaccurate headline of the Chicago Daily Tribune announcing Thomas Dewey’s supposed victory (credit: David Erickson/Flickr).

Most polling companies employ statisticians and methodologists trained in conducting polls and analyzing data. A number of criteria must be met if a poll is to be completed scientifically. First, the methodologists identify the desired population, or group, of respondents they want to interview. For example, if the goal is to project who will win the presidency, citizens from across the United States should be interviewed. If we wish to understand how voters in Colorado will vote on a proposition, the population of respondents should only be Colorado residents. When surveying on elections or policy matters, many polling houses will interview only respondents who have a history of voting in previous elections, because these voters are more likely to go to the polls on Election Day. Politicians are more likely to be influenced by the opinions of proven voters than of everyday citizens. Once the desired population has been identified, the researchers will begin to build a sample that is both random and representative.

A random sample    consists of a limited number of people from the overall population, selected in such a way that each has an equal chance of being chosen. In the early years of polling, telephone numbers of potential respondents were arbitrarily selected from various areas to avoid regional bias. While landline phones allow polls to try to ensure randomness, the increasing use of cell phones makes this process difficult. Cell phones, and their numbers, are portable and move with the owner. To prevent errors, polls that include known cellular numbers may screen for zip codes and other geographic indicators to prevent regional bias. A representative sample    consists of a group whose demographic distribution is similar to that of the overall population. For example, nearly 51 percent of the U.S. population is female.

United States Census Bureau. 2012. “Age and Sex Composition in the United States: 2012.” United States Census Bureau . http://www.census.gov/population/age/data/2012comp.html (February 17, 2016).
To match this demographic distribution of women, any poll intended to measure what most Americans think about an issue should survey a sample containing slightly more women than men.

Pollsters try to interview a set number of citizens to create a reasonable sample of the population. This sample size will vary based on the size of the population being interviewed and the level of accuracy the pollster wishes to reach. If the poll is trying to reveal the opinion of a state or group, such as the opinion of Wisconsin voters about changes to the education system, the sample size may vary from five hundred to one thousand respondents and produce results with relatively low error. For a poll to predict what Americans think nationally, such as about the White House’s policy on greenhouse gases, the sample size should be larger.

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Source:  OpenStax, American government. OpenStax CNX. Dec 05, 2016 Download for free at http://cnx.org/content/col11995/1.15
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