Public opinion polls can be simultaneously compelling and off-putting - compelling because they represent a sort of national look in the mirror; off-putting because they're not well understood by many news consumers. Why conduct polls? How do they work? And how come you never call me? Some basic answers follow.
Why Conduct Polls?
Public opinion is an integral part of the news we cover: It informs and influences political debate, the state of the economy, social trends and more. Simply put, we report what people think, along with what they do, because it is important.
At the ABCNEWS Polling Unit, we are news reporters first; we think of public opinion as our beat - like covering the Supreme Court, the White House or the Pentagon. In many ways the process is the same: We pick a topic, formulate questions, go to our best sources, ask what we need to know and report what we've learned.
The difference is in the selection of our sources. Polling relies on the principles of inferential statistics, which state that we can draw inferences about a set (in this case, the American public) by examining a randomly assembled subset. Random selection is key: The fundamental requirement for any poll to be representative is that it be based on a valid, random sample of respondents.
A National Blood Test
Pollsters have a joke: If you don't believe in random sampling, next time you go to the doctor for a blood test, have him take it all.
You get the point. It only takes a tiny drop of blood, randomly drawn from the body, to test for cholesterol. And it doesn't matter how big the donor is - a mouse, a man, Godzilla. Go even bigger: Imagine someone the size of Mars. No matter. A single drop is still enough to complete the test.
Or imagine a big bowl full of red and yellow jelly beans. You don't have to count them all to know the correct proportion. Just close your eyes, stir thoroughly and pull out a random sample - say, a hundred of them. The share of red to yellow jelly beans in the sample will closely represent the color distribution of all those in the bowl. And it doesn't matter if the bowl fits on your kitchen table, or if it's the size of Yankee Stadium.
Of course, sampling's not perfect. (What is?) A statistical formula produces a margin of error, telling us how close to the full population we can expect the sample to take us. Generally speaking, the larger the random sample, the smaller the sampling error.
Remember, as in the examples above, the error margin does not depend on the size of the population under study (except in the case of very small populations) - only on the size of the random sample itself. That's why a sample of 500 or 1,000 adults, randomly selected, is perfectly adequate to represent the nation's population of 200 million.
You Never Call Me
Our opinion polls start with a computer program that generates a random sample of all possible residential telephone numbers in the country. The survey is designed so that every residential phone has the same probability of getting the call.
So why haven't you been called for an ABCNEWS poll? Because it's a big country, with lots of phones. You've got better odds of getting hit by lightning. The key point is that your odds of getting called are precisely the same as everyone else's.