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Chapter 1: Problem 8

The survey has bias. (a) Determine the type of bias. (b) Suggest a remedy. Suppose you are conducting a survey regarding the sleeping habits of students. From a list of registered students, you obtain a simple random sample of 150 students. One survey question is "How much sleep do you get?"

Short Answer

Expert verified
The type of bias is response bias. Providing more structured multiple-choice options can remedy this bias.

Step by step solution

01

Identify the type of bias

In this scenario, the question 'How much sleep do you get?' may lead to response bias. Response bias occurs because the question is open-ended and subjective, and students might not accurately remember or report their actual sleeping hours. Additionally, students may overestimate their sleeping hours due to social desirability bias, which influences them to provide answers they think are more socially acceptable.
02

Analyze the bias

Response bias can significantly affect the validity of the survey results, leading to an inaccurate assessment of students' sleeping habits. To make the data more reliable, it is crucial to address and minimize this bias.
03

Suggest a remedy for the bias

To minimize response bias, the survey question should be more specific and structured. For instance, converting the question 'How much sleep do you get?' to 'On average, how many hours of sleep do you get per night?' with multiple-choice options like 'Less than 5 hours,' '5-6 hours,' '6-7 hours,' '7-8 hours,' and 'More than 8 hours' could help. This structure makes it easier for students to respond accurately.

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Key Concepts

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

types of bias
Bias in surveys can substantially affect the accuracy and reliability of the results. Several types of bias can occur during data collection:
  • Selection Bias: Occurs when the sample chosen is not representative of the whole population. This can happen if certain groups are underrepresented or overrepresented.
  • Non-Response Bias: Happens when individuals chosen to participate do not respond, leading to a distortion in the survey outcomes as those who did not respond may have different views than those who did.
  • Response Bias: Arises when the responses differ from the truth due to how questions are asked or how respondents perceive their need to answer. This is often caused by poorly worded or leading questions.
Recognizing these biases is crucial because it allows researchers to take steps to mitigate them, thereby improving the validity of their survey results.
response bias
Response bias can significantly skew the results of a survey and usually occurs when questions are not precisely framed or are too subjective. In our example, the question 'How much sleep do you get?' may lead to response bias due to its open-ended nature.
Several factors contribute to response bias:
  • Question Wording: The way a question is phrased can lead respondents to answer in a particular way. For example, leading questions can suggest a preferred response, consciously or subconsciously.
  • Social Desirability: Individuals may provide answers that they believe are more socially acceptable, rather than what is true for them. In the case of asking about sleep, students might overreport their hours to align their answers with perceived norms.
  • Recall Bias: Respondents might not accurately remember past events, such as exact hours of sleep over several nights.
To mitigate response bias, it is crucial to carefully design survey questions and ensure they are as specific and neutral as possible.
survey question design
Designing effective survey questions is a critical step in minimizing bias and obtaining reliable data. Here's how to improve the question 'How much sleep do you get?' to minimize response bias:
  • Be Specific: Narrow down the question to a specific time frame. Instead of asking generally, specify 'On average, how many hours of sleep do you get per night?' This gives respondents a clear timeframe to recall.
  • Provide Multiple-Choice Options: Multiple-choice answers can help respondents provide more accurate responses. For instance, options like 'Less than 5 hours,' '5-6 hours,' '6-7 hours,' '7-8 hours,' and 'More than 8 hours' simplify the answering process and reduce guesswork.
  • Avoid Leading Questions: Ensure questions are neutral and do not imply that one option is better or more socially acceptable than another.
  • Pre-test Your Questions: Before finalizing, test your survey on a small, representative sample to identify any potential issues or misunderstandings.
By aligning survey questions with these principles, the data collected will be more reliable and valid, providing better insights for research.

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Most popular questions from this chapter

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Researchers wanted to determine the association between number of times one chews food and food consumption. They identified 45 individuals who were 18 to 45 years of age. First, the researchers determined a baseline for number of chews before swallowing food. Next, each participant attended three sessions to eat pizza for lunch until comfortably full by chewing each portion of food \(100 \%, 150 \%,\) and \(200 \%\) of their baseline number of chews before swallowing. Food intake for each of the three chewing treatments was then measured. It was found that food consumption was reduced significantly, by \(9.5 \%\) and \(14.8 \%,\) respectively, for the \(150 \%\) and \(200 \%\) number of chews compared to the baseline. (a) What is the research objective of the study? (b) What is the response variable in this study? Is it quantitative or qualitative? (c) What is the explanatory variable in this study? Is it quantitative or qualitative? (d) Who are the experimental units? (e) How is control used in this study? (f) Each individual chewed \(100 \%, 150 \%,\) and \(200 \%\) of their baseline number of chews before swallowing. This is referred to as a repeated-measures study since the same participants were exposed to each treatment. The order in which chewing took place ( \(100 \%\) versus \(150 \%\) versus \(200 \%\) ) was determined randomly. Explain why this is important.
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