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What is a narrow question?

What is a narrow question?

Narrow questions are typically a “Yes” or “No” answer. Examples: “Have you ever had (X Product or Service) before?”

How do you narrow down a research question?

Here are some common ways you can narrow down a research topic:

  1. By demographic characteristics. Narrow it down by age group, occupation, ethnic group, gender, etc.
  2. By relevant issues. Try to identify key issues related to your topic, especially ones that you have an opinion on.
  3. By location.
  4. By timeframe.
  5. By causes.

How do you write a qualitative research question?

Use good qualitative wording for these questions.

  1. Begin with words such as “how” or “what”
  2. Tell the reader what you are attempting to “discover,” “generate,” “explore,” “identify,” or “describe”
  3. Ask “what happened?”
  4. Ask “what was the meaning to people of what happened?”
  5. Ask “what happened over time?”

What are qualitative research questions?

Qualitative research questions differ from quantitative research questions. Qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, so they are often more general and vaguely worded. They may include only one concept, though many include more than one.

What type of data is a yes no question?

Two good examples of nominal data are “yes-no” and “true-false” answers on a survey.

Is yes or no discrete or continuous?

Discrete data can be further sub-divided into three categories: binary, nominal and ordinal. Binary Data: A binary data only takes on two possible values. For example, lamp is on or lamp is off, answer is true or false, 0 or 1, yes or no etc.

What is an example of a qualitative variable?

A qualitative variable, also called a categorical variable, is a variable that isn’t numerical. It describes data that fits into categories. For example: Eye colors (variables include: blue, green, brown, hazel).

What are examples of nominal data?

Examples of nominal data include country, gender, race, hair color etc. of a group of people, while that of ordinal data include having a position in class as “First” or “Second”. Note that the nominal data examples are nouns, with no order to them while ordinal data examples comes with a level of order.

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