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Chapter 8: Problem 36

Seat belt use. A study in El Paso, Texas, looked at seat belt use by drivers. Drivers were observed at randomly chosen convenience stores. After they left their cars, they were invited to answer questions that included questions about seat belt use. In all, \(75 \%\) said they always used seat belts, yet only \(61.5 \%\) were wearing seat belts when they pulled into the store parking lots. 28 Explain the reason for the bias observed in responses to the survey. Do you expect bias in the same direction in most surveys about seat belt use?

Short Answer

Expert verified
Bias results from social desirability, where respondents claim higher seat belt use. This bias is common in surveys on socially favorable behaviors.

Step by step solution

01

Identifying the Bias

The discrepancy between the self-reported data (75%) and observed data (61.5%) suggests the presence of bias. In self-reported surveys, respondents often report behavior that they believe is socially acceptable or desirable, rather than true behavior. This is known as social desirability bias.
02

Analyzing the Social Desirability Bias

Social desirability bias occurs when individuals answer survey questions in a manner that will be viewed favorably by others. In the context of seat belt use, respondents may overreport their use of seat belts because using seat belts is widely seen as responsible and safe driving behavior.
03

Considering the Survey Conditions

The method of surveying immediately after drivers parked may contribute to the bias. Respondents who aren't currently using seat belts might not want to admit it due to the immediate context, increasing the likelihood of overreporting past seat belt use.
04

Generalizing the Bias to Other Surveys

Surveys about socially desirable behaviors, such as seat belt usage, often show bias in the same direction, where self-reported data indicates higher compliance than observed data.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Bias in Surveys
Bias in surveys is a common phenomenon that can significantly impact the accuracy and reliability of survey results. It occurs when the survey design or conduct influences the responses in a way that does not represent the true situation or opinions.
  • Bias can arise from various sources, including the wording of questions, the environment in which surveys are conducted, or even the respondents themselves.
  • In the case of the El Paso seat belt study, the disparity between the self-reported and observed data suggests a bias influenced by the social context of the questions.
  • This highlights how important it is to critically design surveys and analyze the collected data to understand the potential biases that might affect the results.
Understanding and minimizing bias is vital for obtaining data that truly reflects reality. Researchers must take care to design surveys that account for potential sources of bias and apply methods to mitigate them.
Social Desirability Bias
Social desirability bias is a specific type of bias where respondents provide answers that they believe will be viewed favorably by others. This often happens with behaviors that are subject to strong social norms or expectations.
  • In the context of seat belt use in El Paso, drivers might claim they always wear seat belts to reflect the socially accepted norm of safety-conscious driving, even if this behavior is not consistently practiced.
  • This type of bias can lead to overreporting of socially approved behaviors (like wearing seat belts) and underreporting of socially disapproved behaviors.
To reduce social desirability bias, survey designs can include anonymous responses or use indirect questioning techniques that allow respondents to answer more honestly without fear of judgment.
Self-Reported Behavior
Self-reported behavior encompasses data points that individuals provide about their own actions, habits, or patterns. While self-reported data can be invaluable, it is often less reliable due to biases, such as memory recall issues or social desirability bias.
  • As seen in the El Paso study, self-reported seat belt usage did not align with observed behavior, highlighting discrepancies that often arise in this type of data collection.
  • Self-reported behavior should therefore be complemented with objective measures or observations whenever possible, to provide a more accurate and comprehensive understanding.
  • Surveys must be careful to word questions in a way that minimizes bias and encourages honest reporting.
This approach helps ensure that the collected data reflects actual behavior more accurately, giving a true picture of habits or practices.
Observational Studies
Observational studies involve collecting data through direct observation of subjects in their natural settings, without interference or influence from the researchers.
  • They are widely important in research as they produce data that reflects true behaviors and practices, compared to potentially biased self-reported data.
  • In the El Paso study, the observed seat belt use allowed researchers to identify discrepancies between what individuals reported and what was actually occurring.
Observational studies help validate self-reported data and can be used to investigate the extent of biases present. However, they require careful planning and ethical considerations, especially to ensure that the presence of observers does not alter subjects' behaviors.

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Most popular questions from this chapter

Election polls. In response to the question, "If the 2016 presidential elections were being held today, would you vote for Hillary Clinton or Donald Trump?," the New York Times reported the result as \(43 \%\) for Hillary Clinton and \(39 \%\) for Donald J. Trump on July 7, 2016. This result was described as a "National Polling Average." Here are some details on how the average was computed. The New York Times polling averages use all polls currently listed in The Huffingtan Post's polling database. Polls canducted more recently and polls with a larger sample size are given greater weight in computing the averages, and polls with partisan sponsors are excluded. 36 (a) Why do you think they gave greater weight to polls with larger sample sizes? (b) Why should more recent polls be given greater weight? What population were they interested in on July 7, 2016 , and how does that population continue to change over the election period? (c) Why were polls with partisan sponsors excluded?

Wording survey questions. Comment on each of the following as a potential sample survey question. Is the question sufficiently clear? Is it slanted toward a desired response? (a) "In light of skyrocketing gasoline prices, we should consider opening up a very small amount of Alaskan wilderness for oil exploration as a way of reducing our dependence on foreign oil. Do you agree or disagree?" (b) "Do you agree that a national system of health insurance should be favored because it would provide health insurance for everyone and would reduce administrative costs?" (c) "In view of the negative externalities in parent labor force participation and pediatric evidence associating increased group size with morbidity of children in day care, do you support government subsidies for day care programs?"

A Survey of 100,000 Physicians. In 2010 , the Physicians Foundation conducted a survey of physicians' attitude about health care reform, calling the report "a survey of 100,000 physicians." The survey was sent to 100,000 randomly selected physicians practicing in the United States: 40,000 via postoffice mail and 60,000 via email. A total of 2,379 completed surveys were received. 11 (a) State carefully what population is sampled in this survey and what is the sample size. Could you draw conclusions from this study about all physicians practicing in the United States? (b) What is the rate of nonresponse for this survey? How might this affect the credibility of the survey results? (c) Why is it misleading to call the report "a survey of 100,000 physicians"?

A sample of households in a community is selected at random from the telephone directory. In this community, \(4 \%\) of households have no telephone, \(10 \%\) have only cell phones, and another \(25 \%\) have unlisted telephone numbers. The sample will certainly suffer from (a) nonresponse. (b) undercoverage. (c) false responses.

Student opinions. A university has 30,000 undergraduate and 10,000 graduate students. A survey of student opinion concerning health care benefits for domestic partners of students selects 300 of the 30,000 undergraduate students at random and then separately selects 100 of the 10,000 graduate students at random. The 400 students chosen make up the sample. (a) What is the probability that any of the 30,000 undergraduates is in your random sample of 300 undergraduates selected? What is the probability that any of the 10,000 graduate students is in your random sample of 100 graduate students selected? (b) If you have done the calculations correctly in part (a), the probability of any student at the university being selected is the same. Why is your sample of 400 students from the university not an SRS of students? Explain.
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