 are proven to work, sparing the researcher from having to do pretesting (see below). Second, asking the same question allows tracking attitudes or information over time.
Writing new questions requires considerable thought and care. Researcher need to make the question as clear as possible because ambiguous wording can lead some respondents to understand the question one way and others to understand it a different way. If they do, their answers will not be comparable because they “agree” or “disagree” with different statements. Using an interviewer rather than a self-completion questionnaire may not prevent this because many people are reluctant to admit that they do not understand a question. It is also important to avoid double-barrelled questions, questions that ask about two possibilities simultaneously. Any question with the word “or” – as in “Should the government increase the gas tax or leave it at the present level?” – is double-barrelled because a data coder cannot tell whether “yes” or “no” refers to raising the tax or leaving it where it is. However, any question that covers two options – for instance, “would you use the library more if it were open later on weekdays or on the weekend?” – causes the same problem because the coder can’t tell whether a “yes” answer means the respondent would use the library more if it were open later on weekdays, if it were open on weekends, or both. The library budget committee would certainly want to know so it could attract as many users as possible for the additional money spend of staff pay if the library is to be open more hours. Loaded questions, questions in which the first words use language that will encourage respondents to view an issue, problem, group, or individual in a positive or negative light, should also be avoided because they can affect answers. “Should deadbeat dads be put in jail?” has a very different effect on respondents than “Should parents who fail to pay child support be punished?”
Unless they are only using previously-asked questions, pollsters and survey researchers need to try out their questionnaires before using them on a full sample. During pretesting they try out different question wording and different question order with a few individuals to see whether they have trouble understanding the questions, whether the wording or order biases responses, or causes any other problems. If they have a particularly long or complex set of questions, they will pretest parts of the questionnaire and then conduct a pilot – ask a few individuals to answer all of the questions. A good pilot checks out all the phases of survey research – drawing a small sample, administering the questionnaire, and coding the responses for analysis. Doing so allows the lead researchers designing the survey project to make sure that any assistants who will be helping administer the questionnaire or code the data complete those steps as the lead researchers expect.
Reporting the Results
Polls are more likely to be reported in the media than surveys, though sometimes particular questions used in a survey are so interesting that journalists write about them and use the survey data in their stories.
Both polls and surveys ask a sample of people to estimate the attitudes in a larger population. Thus news stories seldom say that some percentage of those polled or surveyed gave some particular answer; they report that some percent of the relevant population (Americans, football fans, senior citizens, whatever) shares that opinion. Estimates of public opinion can be reported as point estimates – single numbers saying what percent of the population would answer the question a particular way (as in “39% of the voters in Ohio will vote yes on Question 1”) – or as an interval – a range of numbers giving the high and low estimate (as in “between 37 and 41% of the voters will vote yes on Question 1”). The point estimate treats the sample as if it exactly matches the population; the interval estimate acknowledges that even with a carefully-selected random sample that is not biased in any way it