According to 2008 data, 19.1 percent of Americans exclusively had a landline telephone, 63.2 percent had both a landline and a cell phone, and 14.5 percent only had a cell phone [source: Lambert]. Since cell phones are almost always unlisted, pollsters like ABC News randomly dial numbers in known cell phone-only exchanges and weight those responses separately against the landline sample. Rasmussen Reports, another national polling organization, uses online polls to reach people who have abandoned traditional landline phones altogether [source: Rasmussen Reports].
Getting a Representative Sample
The mission of political polling is to gauge the political opinion of the entire nation by asking only a small sample of likely voters. For this to work, pollsters have to ensure that the sample group accurately represents the larger population. If 50 percent of voters are female, then 50 percent of the sample group needs to be female. The same applies to characteristics like age, race and geographic location.
To get the most accurate representative sample, political pollsters take a page from probability theory [source: Zukin]. The goal of probability theory is make mathematical sense out of seemingly random data. By creating a mathematical model for the data, researchers can accurately predict the probability of future outcomes. Political pollsters are trying to come up with models that accurately predict the outcome of elections. To do that, they need to start with a perfectly random sample and then adjust the sample so that it closely matches the characteristics of the entire population.
The most popular method for achieving a random sample is through random digit dialing (RDD). Pollsters start with a continually updated database of all listed telephone numbers in the country -- both landline and cell phones. If they only called the numbers in the database, then they'd exclude all unlisted numbers, which wouldn't be a truly random sample. Using computers, pollsters analyze the database of listed numbers to identify all active blocks of numbers, which are area codes and exchanges (the second three digits) actively in use [source: Langer]. The computers are then programmed to randomly dial every possible number combination in each active block.
For a truly random sample, pollsters not only need to dial random numbers, but choose random respondents within the household. Statistics show that women and older people are far more likely to answer the phone than other Americans [source: Zukin]. To randomize the sample, political pollsters often ask to speak to the member of the house with the most recent birthday.
Once a political polling organization has collected responses from a sufficiently random sample, it must adjust or weight that sample to match the most recent census data about the sex, age, race, and geographical breakdown of the American public. We'll talk more about weighting in a later section, but first, let's settle some of the mystery behind margins of error.