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Pollsters can reduce sampling error by administering a poll to a larger sample. For example, a sample of 10,000 drawn from the 1,000,000-member population would yield an MSE of +/-1% at the 95% confidence level, and a sample of 100,000 would reduce the MSE to just +/-0.3%. In practice, however, increasing sample size usually entails financial and logistical costs that are not offset by lower sampling error.  
Pollsters can reduce sampling error by administering a poll to a larger sample. For example, a sample of 10,000 drawn from the 1,000,000-member population would yield an MSE of +/-1% at the 95% confidence level, and a sample of 100,000 would reduce the MSE to just +/-0.3%. In practice, however, increasing sample size usually entails financial and logistical costs that are not offset by lower sampling error.  


Sampling error does not reflect other potential sources of inaccuracy, including sampling bias, or the administration of a poll to a sample that is not representative of the population as a whole.
Sampling error does not reflect other potential sources of inaccuracy, including sampling bias, which comes about when a poll is administered to a sample that is not representative of the population as a whole.


===Nonresponse bias===
===Nonresponse bias===

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A public opinion poll is a questionnaire used to measure public opinion, or the attitudes held collectively by a population. Because of the impracticality of administering the questionnaire to all of a large population's members, public opinion polls assess the opinions of the total population by surveying a sample of size N, where N is sufficiently large and representative to produce statistically valid results. Unscientific public opinion polls, which collect information from a haphazard sample, date back at least to the use of straw polls to predict American election results in the 1820s. Once modern statistical sampling theory was invented around 1930, George Gallup and other advertisers started to create nationwide public opinion polls, using about 1500 cases. The American public became fascinated with polls, which spread to many democratic countries by 1940. Totalitarian countries did not allow them.

History of opinion polls

The first known example of an opinion poll was a local straw vote conducted by a newspaper The Harrisburg Pennsylvanian in 1824; it showed Andrew Jackson leading John Quincy Adams by 335 votes to 169 in the contest for the presidency. Such straw votes—unweighted and unscientific— gradually became more popular; but they remained local, usually city-wide phenomena. In 1916, the large-circulation U.S. magazine 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 called the following four presidential elections.

In 1936, however, the Digest came unstuck. 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 saw the bias but did not know how to correct it. The week before election day, it reported that Alf Landon was far ahead of Franklin D. 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 went out of business soon afterwards, while the polling industry started to take off .

Gallup launched a subsidiary in Britain, where it correctly predicted Labour's victory in the 1945 general election, in contrast with virtually all other commentators, who expected the Conservative Party, led by Winston Churchill, to win easily.

By the 1950s, polling had spread to most democracies. Nowadays they reach virtually every country, although in more autocratic societies they tend to avoid sensitive political topics. In Iraq, surveys conducted soon after the 2003 war helped measure the true feelings of Iraqi citizens to Saddam Hussein, post-war conditions and the presence of US forces.

For many years, opinion polls were conducted mainly face-to-face, either in the street or in people's homes. This method remains widely used, but in some countries it has been overtaken by telephone polls, which can be conducted faster and more cheaply. Because of the common practice of telemarketers to sell products under the guise of a telephone survey and due to the proliferation of residential call screening devices and use of cell phones, response rates for phone surveys have been plummeting. Mailed surveys have become the data collection method of choice among local governments that conduct a citizen survey to track service quality and manage resource allocation. In recent years, Internet and short message service (SMS, or text) surveys have become increasingly popular, but most of these draw on whomever wishes to participate rather than a scientific sample of the population, and are therefore not generally considered accurate.

Potential for inaccuracy

Sampling error and bias

All polls administered to samples are subject to sampling error, which refers to the extent to which the opinions expressed by the surveyed sample do not reflect the opinions of the population as a whole. Sampling error is typically expressed as a confidence interval of plus or minus some number of percentage points associated with a statistical confidence level. For example, the maximum sampling error (MSE) for a sample of 1050 drawn from a population of 1,000,000 is +/-3 percentage points at the 95% confidence level; this means that there's a 95 percent chance that the results of a survey administered to that sample fall within a 6-point range around the true opinion of the population as a whole.

Pollsters can reduce sampling error by administering a poll to a larger sample. For example, a sample of 10,000 drawn from the 1,000,000-member population would yield an MSE of +/-1% at the 95% confidence level, and a sample of 100,000 would reduce the MSE to just +/-0.3%. In practice, however, increasing sample size usually entails financial and logistical costs that are not offset by lower sampling error.

Sampling error does not reflect other potential sources of inaccuracy, including sampling bias, which comes about when a poll is administered to a sample that is not representative of the population as a whole.

Nonresponse bias

Since some people do not answer calls from strangers, or refuse to answer the poll, poll samples may not be representative samples from a population. Because of this selection bias, the characteristics of those who agree to be interviewed may be markedly different from those who decline. That is, the actual sample is a biased version of the universe the pollster wants to analyze. In these cases, bias introduces new errors, one way or the other, that are in addition to errors caused by sample size. Error due to bias does not become smaller with larger sample sizes. If the people who refuse to answer, or are never reached, have the same characteristics as the people who do answer, the final results will be unbiased. If the people who do not answer have different opinions then there is bias in the results. In terms of election polls, studies suggest that bias effects are small, but each polling firm has its own formulas on how to adjust weights to minimize selection bias.[1]

Response bias

Survey results may be affected by response bias, where the answers given by respondents do not reflect their true beliefs. This may be deliberately engineered by unscrupulous pollsters in order to generate a certain result or please their clients, but more often is a result of the detailed wording or ordering of questions (see below). Respondents may deliberately try to manipulate the outcome of a poll by e.g. advocating a more extreme position than they actually hold in order to boost their side of the argument or give rapid and ill-considered answers in order to hasten the end of their questioning. Respondents may also feel under social pressure not to give an unpopular answer. For example, respondents might be unwilling to admit to unpopular attitudes like racism or sexism, and thus polls might not reflect the true incidence of these attitudes in the population. If the results of surveys are widely publicised this effect may be magnified - the so-called "spiral of silence."

Wording of questions

It is well established that the wording of the questions, the order in which they are asked and the number and form of alternative answers offered can influence results of polls. Thus comparisons between polls often boil down to the wording of the question. On some issues, question wording can result in quite pronounced differences between surveys. [2][3][4] This can also, however, be a result of legitimately conflicted feelings or evolving attitudes, rather than a poorly constructed survey.[5] One way in which pollsters attempt to minimize this effect is to ask the same set of questions over time, in order to track changes in opinion. Another common technique is to rotate the order in which questions are asked. Many pollsters also split-sample. This involves having two different versions of a question, with each version presented to half the respondents.

The most effective controls, used by attitude researchers, are:

  • asking enough questions to allow all aspects of an issue to be covered and to control effects due to the form of the question (such as positive or negative wording), the adequacy of the number being established quantitatively with psychometric measures such as reliability coefficients, and
  • analyzing the results with psychometric techniques which synthesize the answers into a few reliable scores and detect ineffective questions.

These controls are not widely used in the polling industry.

Coverage bias

Another source of error is the use of samples that are not representative of the population as a consequence of the methodology used, as was the experience of the Literary Digest in 1936. For example, telephone sampling has a built-in error because in many times and places, those with telephones have generally been richer than those without. Alternately, in some places, many people have only mobile telephones. Because pollers cannot call mobile phones (it is unlawful to make unsolicited calls to phones where the phone's owner may be charged simply for taking a call), these individuals will never be included in the polling sample. If the subset of the population without cell phones differs markedly from the rest of the population, these differences can skew the results of the poll. Polling organizations have developed many weighting techniques to help overcome these deficiencies, to varying degrees of success. Several studies of mobile phone users by the Pew Research Center in the U.S. concluded that the absence of mobile users was not unduly skewing results, at least not yet. [6]

An oft-quoted example of opinion polls succumbing to errors was the British election of 1992. Despite the polling organisations using different methodologies virtually all the polls in the lead up to the vote (and exit polls taken on voting day) showed a lead for the opposition Labour party but the actual vote gave a clear victory to the ruling Conservative party.

In their deliberations after this embarrassment the pollsters advanced several ideas to account for their errors, including:

  • Late swing. The Conservatives gained from people who switched to them at the last minute, so the error was not as great as it first appeared.
  • Nonresponse bias. Conservative voters were less likely to participate in the survey than in the past and were thus underrepresented.
  • The spiral of silence. The Conservatives had suffered a sustained period of unpopularity as a result of economic recession and a series of minor scandals. Some Conservative supporters felt under pressure to give a more popular answer.

The relative importance of these factors was, and remains, a matter of controversy, but since then the polling organisations have adjusted their methodologies and have achieved more accurate predictions in subsequent elections.

Polling organizations

There are many polling organizations. The most famous remains the very first one, the Gallup Organization, which was created by George Gallup in 1935.

Other major polling organizations in the U.S. include:

In Britain the most notable "pollsters" are:

  • MORI. This polling organisation is notable for only selecting those who say that they are "likely" to vote. This has tended to favour the Conservative Party in recent years.
  • YouGov, an online pollster.
  • GfK NOP
  • ICR
  • ICM
  • Populus, official The Times pollster.

In Australia the most notable companies are:

In Canada the most notable companies are:

In Nigeria the most notable polling organization is:

All the major television networks, alone or in conjunction with the largest newspapers or magazines, in virtually every country with elections, operate polling operations, alone or in groups.

Several organizations monitor the behaviour of pollsters and the use of polling data, including PEW and, in Canada, the Laurier Institute for the Study of Public Opinion and Policy.[7]

The best-known failure of opinion polling to date in the U.S. was the prediction in 1948 that Thomas Dewey would defeat Harry S. Truman. Major polling organizations, including Gallup and Roper, indicated a landslide victory for Dewey.

In britain, most polls failed to predict the Conservative election victories of 1970 and 1992, and Labour's victory in 1974. However, their figures at other elections have been generally accurate.

The influence of opinion polls

By providing information about voting intentions, opinion polls can sometimes influence the behaviour of electors. The various theories about how this happens can be split up into two groups: bandwagon/underdog effects, and strategic ('tactical') voting.

A Bandwagon effect occurs when the poll prompts voters to back the candidate shown to be winning in the poll. The idea that voters are susceptible to such effects is old, stemming at least from 1884; Safire (1993: 43) reported that it was first used in a political cartoon in the magazine Puck in that year. It has also remained persistent in spite of a lack of empirical corroberation until the late 20th century. George Gallup spent much effort in vain trying to discredit this theory in his time by presenting empirical research. A recent meta-study of scientific research on this topic indicates that from the 1980's onward the Bandwagon effect is found more often by researchers (Irwin & van Holsteyn 2000).

The opposite of the bandwagon effect is the Underdog effect. It is often mentioned in the media. This occurs when people vote, out of sympathy, for the party perceived to be 'losing' the elections. There is less empirical evidence for the existence of this effect than there is for the existence of the Bandwagon effect (Irwin & van Holsteyn 2000).

The second category of theories on how polls directly affect voting is called strategic or tactical voting. This theory is based on the idea that voters view the act of voting as a means of selecting a government. Thus they will sometimes not choose the candidate they prefer on ground of ideology or sympathy, but another, less-preferred, candidate from strategic considerations. An example can be found in the general election of 1997. Then Cabinet Minister, Michael Portillo's constituency of Enfield was believed to be a safe seat but opinion polls showed the Labour candidate Stephen Twigg steadily gaining support, which may have prompted undecided voters or supporters of other parties to support Twigg in order to remove Portillo. Another example is the Boomerang effect where the likely supporters of the candidate shown to be winning feel that s/he is "home and dry" and that their vote is not required, thus allowing another candidate to win.

These effects only indicate how opinion polls directly affect political choices of the electorate. Other effect can be found on journalists, politicians, political parties, civil servants etc. in, among other things, the form of media framing and party ideology shifts.

Bibliography

Primary sources

  • Cantril, Hadley and Mildred Strunk, eds. Public Opinion, 1935-1946 (1951), massive compilation of many public opinion polls from US, Britain, Canada, Australia, and elsewhere.
  • Gallup, Alec M. ed. The Gallup Poll Cumulative Index: Public Opinion, 1935-1997 (1999) lists 10,000+ questions, but no results
  • Gallup, George Horace, ed. The Gallup Poll; Public Opinion, 1935-1971 3 vol (1972) summarizes results of each poll.

External links

References

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