The size of the sample in a qualitative study is typically smaller than that in a quantitative study. This is because the goal of a qualitative study is to gather rich, in-depth data that provides a deep understanding of the research question, rather than generalizable findings that can be applied to a larger population (Grove, Burns, & Gray, 2013).
In qualitative research, the researcher stops collecting data when they have obtained enough rich and meaningful data to achieve the study aims. This is known as saturation, which is reached when new data no longer provide additional insights or contribute to further understanding of the research question (Grove, Burns, & Gray, 2013).
On the other hand, in quantitative studies, a larger sample size is often required to generate sufficient statistical power to demonstrate significance. Statistical power refers to the ability to detect a true relationship or difference in a sample, if it exists in the population (Grove, Burns, & Gray, 2013). Therefore, larger sample sizes are needed to achieve adequate statistical power, particularly when detecting small effects or when the variability within the sample is high.
That being said, small-scale quantitative studies may be considered less reliable due to the low quantity of data. With a smaller sample size, the potential for sampling error and bias increases, which can affect the accuracy and generalizability of the findings (Mcleod, 2018). However, small-scale quantitative studies can still provide valuable insights and contribute to the existing body of knowledge, particularly in areas where limited research has been conducted.
To illustrate the difference between qualitative and quantitative research, let’s consider two research questions related to eating disorders, specifically bulimia nervosa.
The qualitative research question would aim to explore the perceptions of eating disorder patients with bulimia nervosa towards cognitive-behavioral therapy during their inpatient stay. In this case, the researcher would select a small sample of patients who are in an inpatient setting and conduct interviews with them. The questions asked would be open-ended, allowing the patients to express their thoughts and experiences without influencing their responses (Grove, Burns, & Gray, 2013).
On the other hand, the quantitative research question would investigate how the side effects of bulimia nervosa impact the overall health of patients with an eating disorder. To explore this question, the researcher would need to gather data from a larger sample of diagnosed patients. The research would involve examining existing literature on the side effects of the illness and comparing it with statistical data collected from an inpatient unit that treats eating disorder patients. This approach would help provide a comprehensive understanding of the disease’s impact and allow for comparisons between research findings and real-life examples (Grove, Burns, & Gray, 2013).
In summary, the sample size in qualitative research is smaller because the aim is to obtain rich and meaningful data to achieve the study’s objectives. In contrast, quantitative studies often require larger sample sizes to achieve adequate statistical power. While small-scale quantitative studies may have limitations in terms of reliability, they can still contribute valuable insights in areas where research is limited. Both types of research methodologies have their strengths and can provide valuable contributions to the field of study.