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  2. Total survey error - Wikipedia

    en.wikipedia.org/wiki/Total_survey_error

    Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection, data processing and estimation methods.

  3. Response bias - Wikipedia

    en.wikipedia.org/wiki/Response_bias

    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.

  4. Survey data collection - Wikipedia

    en.wikipedia.org/wiki/Survey_data_collection

    The entire data collection period is significantly shortened, as all data can be collected and processed in little more than a month. [2] Interaction between the respondent and the questionnaire is more dynamic compared to e-mail or paper surveys. [16] Online surveys are also less intrusive, and they suffer less from social desirability effects ...

  5. Questionnaire for User Interaction Satisfaction - Wikipedia

    en.wikipedia.org/wiki/Questionnaire_for_User...

    This was not acceptable since these comments are often vital for usability testing. In response to this need, QUIS Version 5.5 collected and stored comments online for each set of questions. The output format of the QUIS data was also a source of frustration. The original format made analysis confusing and error-prone.

  6. Survey sampling - Wikipedia

    en.wikipedia.org/wiki/Survey_sampling

    Non-response bias: When individuals or households selected in the survey sample cannot or will not complete the survey there is the potential for bias to result from this non-response. Nonresponse bias occurs when the observed value deviates from the population parameter due to differences between respondents and nonrespondents. [12] Response ...

  7. Bias (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bias_(statistics)

    Depending on the type of bias present, researchers and analysts can take different steps to reduce bias on a data set. All types of bias mentioned above have corresponding measures which can be taken to reduce or eliminate their impacts. Bias should be accounted for at every step of the data collection process, beginning with clearly defined ...

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