3.5. Mix of Methods — Comprehensive Notes

There is an ongoing debate about which research method is better: quantitative or qualitative (Veal, 2018, pp. 43–44).
Quantitative research produces results that are mathematically precise and easier to understand (Saunders et al., 2019, p. 175).
It also allows for representative samples, so findings can often be generalized to larger populations (Veal, 2018, p. 53).
For example, election polls can not only show current party preferences but also help forecast results.
Qualitative research, in contrast, explores topics more deeply. It helps understand preferences, motives, attitudes, and perspectives (Saunders et al., 2019, pp. 175, 179).
Quantitative studies may be accurate but can be superficial, because they reduce complex human behavior to numbers (Guba & Lincoln, 1994, pp. 105–106).
On the other hand, qualitative research is sometimes criticized for producing anecdotal evidence, essentially “stories” rather than measurable results, and is occasionally questioned for its scientific rigor.

A key difference between the two main research approaches is their purpose: quantitative research is mainly used to test and either confirm or disprove existing theories, while qualitative research is used to develop new theories, especially in areas where little research has been done (Veal, 2018, pp. 135–136).
There is no single “best” method. Each approach has strengths depending on the topic and research question (Bell, 2018, pp. 25–26).
In fact, many researchers recommend combining both methods, which is called triangulation.
For example, in student evaluations or service satisfaction studies, participants may first answer a standardized questionnaire (quantitative part) and then share their personal opinions in an open text box (qualitative part).
This approach: Combines the strengths of both methods while reducing their weaknesses. Produces more valuable and complete results, as the quantitative part shows general patterns, while the qualitative part gives deeper insights not captured by numbers alone (Veal, 2018, pp. 157–158).

There is no single best method. Each approach has strengths depending on the topic and research question.
Triangulation, by combining quantitative and qualitative methods, is recommended to enhance validity and comprehensiveness of findings.
Quantitative emphasis on generalizable patterns complements qualitative emphasis on depth and context.
Researchers should pay attention to potential divergences between what numbers show and what narratives reveal, and interpret results with awareness of method-specific limitations.

Election polls as an illustration of quantitative precision and the capacity to forecast outcomes.
Student evaluations or service satisfaction studies illustrating triangulation: quantitative survey data plus qualitative open-ended responses.
The combined approach yields results that are not only generalizable but also rich in contextual meaning.