The main methods of presenting numerical data are through graphs, tables and text incorporation. Qualitative data, or data that cannot translate into quantifiable measurements, requires thematic analysis to report patterns appearing in a theme or category.
Graphs use visual elements to make large numbers and complex information more comprehensible. They efficiently display large amounts of data and help in identifying and interpreting patterns in the data. The common types of graphs are the bar graph, pie charts, line graphs and scatter plots. Each type has a different function in displaying data, such as for showing comparisons, analyzing proportional distributions, identifying changes over time and clarifying the connection between two numerical measurements.
Tables are recommended for relatively smaller amounts of values that belong to a single category. Whereas graphs provide a quick overview of data, tables can emphasize these values. Incorporating data in texts even exceeds such level of emphasis, especially when there are only two values to present. As long it succeeds in communicating the results and interpretations to the audience, the researcher can use any of these methods of presenting data.
When dealing with qualitative data, the researcher presents findings and meaningful patterns in a theme before supporting them through existing studies in subsequent discussions. Alternatively, the research may merge the presentation and discussion into one section. The goal of either approach is to convince the reader that the thematic analysis is valid.