How to make data presentation efficient and interesting?
by Sandeep Phatak - Research Associate, Army Audiology and Speech Center at Walter Reed Army Medical Center
- Most readers and listeners are interested in your interpretation of the data and not the raw data itself. Stay focused on presentation of concepts and interpretations as opposed to the raw data itself.
- Do not overwhelm your poster or slides with excessive text. A simple rule would be to not use more than three major text bullets on a slide. Remember - a picture is worth a thousand words!
- Start your presentation with background and motivation for your research work. This is essential to get readers/listeners interested in your presentation. Review the past work, leading to the research question(s) that you worked on. Use an online journal database to search for the relevant publications, including PhD dissertations, journal articles and conference proceedings. Cite references wherever necessary.
- Provide a brief description of your research framework (e.g. experiment/survey design), followed by data analysis. Use figures and graphs to show results of data analysis, rather than tables with raw numbers.
- Choose the right type of plotting method (e.g. lines/bars/pie). For example, pie charts are best for displaying percentages of different categories in a dataset whereas line graphs are best when the data on the x-axis represent magnitude of the same entity/variable. When the data points are across different conditions, the points cannot be connected to form lines. In such cases, bar graphs should be used. In all cases, don't forget to label axes!
- Provide your interpretation of the results and interweave past work based on your literature review mentioned above. Your ability to carefully interpret the data will determine the quality of your research work. Provide bulleted conclusions.
- It is important to close the loop by restating the question(s) answered by your research as well stating those which remain unanswered. You may want to propose follow-up work under the title of "Future Work."
ProQuest Dissertations and Thesis Database.
Online digital libraries such as Proquest, PubMed and Ovid.