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Research Question Examples for Quantitative Studies

Updated: Jun 13, 2022

Every research paper begins with a question. The kind of question that you can ask depends upon the conventions of the academic field that you’re working in. In general, if you’re in a quantitative field, you can think of your question as a specific problem to solve. This means that your question should have well-defined key terms, it should identify a manageable dataset, and ultimately, you should be able to imagine an experimental method to yield an answer. As a student in English, I most often encounter quantitative research questions in the field of Digital Humanities (DH), which uses computer science to answer questions about history and literature. This blog will offer examples of bad, mediocre, and good entry-level DH research question examples for quantitative studies - using Victorian novels as an example topic.


Bad question: Do characters in Victorian novels have a lot of friends?

Explanation: This question does not define its key terms. What “characters” are we talking about, and what counts as “a lot”? Who counts as a “friend”– that is, what is the criteria for friendship in this study? Further, this question has an ill-defined dataset. “Victorian novels” is a massive, ambiguous category. It should be smaller, better defined, and accessible (that is, available in digital form) for the purposes of a DH study.

Bad question: What counts as having a lot of friends in a Victorian novel?

Explanation: This revised question attempts to narrow in on and fix one of the problems in my first bad example above. However, it still fails to define most of its key terms (e.g., friend) and uses an unmanageable dataset.

Bad question: What are the qualities of friendship in Victorian novels?

Explanation: This question is more self-aware, focusing on the key term “friendship” in an effort to define it. However, it’s still in rough shape. Beyond the problems of its dataset being unmanageable, this question is not suited to the field of DH. It would be far easier to describe the “qualities of friendship” by writing a traditional “close reading” or literary analysis paper and then using this research to eventually work towards a DH version of this question. The lesson here is to make sure that your research questions make sense in your given field.

Mediocre question: What counts as having a lot of friends in Dickens’s novels?

Explanation: This question is almost a strong starting point for a research paper. It identifies a manageable and accessible (digitized, open-source) dataset: Dickens’s novels. It also is the kind of question that suits its field—since it would take a lot of counting to answer this question, it makes sense to use some simple code and a spreadsheet rather than keeping track of characters manually. However, there are still ways in which this question could be improved. The author needs to define “friends” in either the paper or the question. What level of human connection counts as a friendship? Can family members be friends too? If so, does this mean that characters with big families will always have the most friends? For Dickens, whose protagonists are often displaced from their families, this could be a real problem. Further, since Dickens’s novels often follow their protagonists through their whole lives, how should you count characters who show up as “friends” for only a chapter or two—or characters who turn into enemies later in life?

Mediocre question: How many friends do Dickens’s main characters have in their first year of life?

Explanation: Again, this question is nearly there. It asks about a specific, bounded period in the characters’ lives, solving one of the problems with the previous question. It also narrows the dataset by focusing on “main characters.” The author of this research question will need to clearly explain their criteria for labeling “main characters” in the body of their paper, but that’s okay—every author has to define their criteria in this way. The real problems with this question are twofold. First, it is still vague about the key term “friends.” The question really should define that term, since it is the focal point of the study. Second, and more importantly, this question lacks a clear motive. Why does it matter how many friends Dickens’s main characters have in their first year of life? If the author’s interest, in general, is to find out what friendship looks like in Victorian novels, then why is this author only focusing on one year (a portion of one chapter, in many books)? The lesson to take away from this question is to always keep your larger research interest in mind, and remember that it is possible to be too narrow in your research question. Don’t be pedantic and lose sight of your goal!

Good Question: What are the top five most frequent nouns that Dickens’s child characters use to refer to their acquaintances at school versus at work in each of his novels?

Explanation: This question has a narrow dataset—it looks at Dickens’s child characters—with the caveat that the author will have to explain their criteria for who counts as a child in their research paper’s introduction. The dataset is further bounded and appropriate to a quantitative DH study since it addresses a specific kind of word (nouns), puts a cap on how many it cares about (five), and clarifies that the author will keep track of the terms in each novel separately. There’s a clear method available to answer this question. All it would take is some simple text tagging, counting code, and a spreadsheet.

More importantly, the question signals its awareness that the term “friendship” itself needs some attention. Instead of taking the meaning of the word “friend” for granted, this question gives the author room to find out if and when Dickens himself uses the word “friend” and in comparison with what other words. Sometimes, in order to get at your main topic of interest (e.g. what “friendship” looks like) it is important to recognize that your dataset may not use the same words that you do; you have to remain open to surprises in your results.

Last, and most impressive, is this question’s clear motive for seeking results. The author is clearly aware that, in Dickens’s fictional worlds, children often have very different relationships with individuals at school and at work. This study may not only tell a story about friendships in Dickens’s novels—it may also yield insights about class, the psychology of child labor vs education, and the ways in which being at work influences children’s social development in Dickens’s fictional worlds. These results would likely be of interest to scholars in a wide range of fields.


As you can see, the qualities that make an entry-level quantitative research question “good” are many. A quantitative research question should have…

  • a clear, manageable, and accessible dataset

  • clear awareness of the characteristics of population from which the author will collect data (e.g., the settings of Dickens’s fictional worlds)

  • well-defined key terms

  • an implied method that the author can achieve within their field

  • a motive

  • the potential to interest other scholars

  • the potential to yield results that will surprise the author

That’s a lot! If you’re interested in developing a quantitative research question, and you would appreciate some guidance in making sure that your question fits these guidelines, CRI’s Research Mentors would love to hear from you! For more information, you can book a session with CRI or plan to work on a research project with us from start-to-finish.

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