Mixed methods involve the use of both the qualitative and quantitative research methodology in the collection and analysis of research data (Johnson & Onwuegbuzie, 2004). The qualitative research design involves descriptive/exploratory statistics, while quantitative involves the use of hard numbers and results that are provable. The use of mixed methods in data collection offers some advantages and disadvantages in the interpretation of research data.
Mixed methods data is often comprehensive as it incorporates both qualitative and quantitative data. The use of mixed methods data provides a meaningful and broad way in which research phenomena can be interpreted. Moreover, (Johnson & Onwuegbuzie, 2004) points with an appropriate design, mixed methods data can mirror the findings of the individual research designs. This can act as an advantage since it acts as a way of validating research data.
However, mixed methods data interpretation can be challenging and time intensive since their interpretations and data are often abstract (Johnson & Onwuegbuzie, 2004). The quantitative data often tries to answer one consistent truth. In contrast, the qualitative data is focused on several answers. Thos can lead to analysis of different problems.
Moreover, the use of mixed methods and its data interpretation requires training and mastery of both research designs (Johnson & Onwuegbuzie, 2004). The authors further note mixed methods data interpretation can be subject to bias. Since people are often different, some may be more adept in performing in one research methodology than the other. For example, a researcher could be more competent in using quantitative than qualitative research design. The difference in the levels of knowledge in the two research designs is a great source of bias in interpretation of mixed methods data.