When working with Likert scale responses in a perception study, summarizing the data can be a crucial step in understanding the results. As a PhD student, I’ve encountered this exact problem in my dissertation. I used a 5-point Likert scale for about 50 questions, and now I’m unsure of the best way to summarize the central tendency and variation of the responses.
Should I use means and standard deviations, or report medians and interquartile ranges? Both approaches have been used in the literature, but which one is more suitable for my study?
To answer this, let’s dive into the characteristics of my data. Since I’m working with ordinal data, using means and standard deviations might not be the best choice. Medians and interquartile ranges, on the other hand, are more robust and can provide a better representation of the data.
However, there are some cases where means and standard deviations might be more appropriate. For instance, if the data is normally distributed or if I’m comparing the results across different groups.
Ultimately, the choice between means and medians depends on the research question, the characteristics of the data, and the goals of the study. As researchers, it’s essential to understand the strengths and limitations of each approach and choose the one that best fits our needs.
So, what’s your take on this? Have you encountered similar challenges in your research? Share your experiences and insights in the comments below!