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It is often argued that open-ended questions (i.e. questions that elicit more than a yes/no answers) are preferable because they open up discussion and enquiry. Peter Worley argues that this is a false assumption. This is based on Worley's central arguments that there are two different kinds of open and closed questions: grammatical and conceptual.
A survey using a Likert style response set. This is one example of a type of survey that can be highly vulnerable to the effects of response bias. Response bias is a general term for a wide range of tendencies for participants to respond inaccurately or falsely to questions.
The types of questions (e.g.: closed, multiple-choice, open) should fit the data analysis techniques available and the goals of the survey. The manner (random or not) and location (sampling frame) for selecting respondents will determine whether the findings will be representative of the larger population .
Therefore, non-response bias may make the measured value for the workload too low, too high, or, if the effects of the above biases happen to offset each other, "right for the wrong reasons." For a simple example of this effect, consider a survey that includes, "Agree or disagree: I have enough time in my day to complete a survey."
Argumentative Questions can also impact the outcome of a survey. These types of questions, depending on their nature, either positive or negative, influence respondents' answers to reflect the tone of the question(s) and generate a certain response or reaction, rather than gauge sentiment in an unbiased manner. [25]
Open questions are those questions that invite the respondent to provide answers in their own words and provide qualitative data. Although these types of questions are more difficult to analyze, they can produce more in-depth responses and tell the researcher what the participant actually thinks, rather than being restricted by categories.
Pollsters have learned at great cost that gathering good survey data for statistical analysis is difficult. The selective effect of cellular telephones on data collection (discussed in the Overgeneralization section) is one potential example; If young people with traditional telephones are not representative, the sample can be biased.
A probability-based survey sample is created by constructing a list of the target population, called the sampling frame, a randomized process for selecting units from the sample frame, called a selection procedure, and a method of contacting selected units to enable them to complete the survey, called a data collection method or mode. [10]