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What are Multiple-Choice Questions? Definition & Example

Multiple-choice questions (= multiple responses) are a form of closed-ended questions where respondents can select more than one answer from predefined categories.

by Maria MalzewUpdated July 26, 2023Reading time 1 min

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When developing a questionnaire for a standardized survey, researchers must not only find the right wording but also determine the appropriate question type for each item. When respondents are allowed to select more than one answer from predefined categories, multiple-choice questions are used.

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General Definition of Multiple-Choice Questions

Multiple-choice questions (= multiple responses) are a form of closed-ended questions where respondents can select more than one answer from predefined categories. In the question phrasing, there should always be a clear indication that informs the respondent about the possibility of multiple responses. Typically, a brief note such as "multiple responses possible" or "you can mark several answers here" is sufficient.

 

Multiple-choice question in a questionnaire of an online survey

 

Typical Use of Multiple-Choice Questions

In empirical research, multiple-choice questions belong to a special category of nominally scaled selection questions, with which non-metric data are collected. While normally the nominally scaled attribute values must be mutually exclusive (= respondents must decide on female, male, or diverse when asked about gender), in this special case multiple simultaneous answers on the nominal scale are possible. However, the data obtained also serve in the multiple-choice variant merely for the categorization of facts and cannot be arranged hierarchically:


Which social media platforms are you registered as a user? You can select multiple answers here.

Answer options:

  1. Facebook
  2. Instagram
  3. Twitter
  4. Tumblr
  5. Tik Tok
  6. LinkedIn
  7. Xing
  8. YouTube
  9. Snapchat
  10. Pinterest
  11. Reddit
  12. Twitch

 

In the evaluation, each category is assigned a numerical value, e.g. Facebook - 1, Instagram - 2, Twitter - 3, etc. With such an assignment, the categories can be better categorized, but the numbers have no further metric significance. From nominal data, it is usually calculated how frequently a particular attribute value occurs.

 

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