Describe the image above
The answer you gave to the question above produces qualitative data. Researchers, are able to interpret a participant’s beliefs and opinions when using this method. Whereas a simple closed question like “Is this a picture of a cake?” produces answers which need to be coded or categorised numerically (Willig, 2009). This produces quantitative data. Studies which generate qualitative or quantitative data are both valid scientific research methods. The only difference is, qualitative methods requires a more creative mind to understand findings and is more time consuming to analyse. Quantitative measures produces data which is more ridged in terms of interpretation. This is a less hands on approach to data collection, in comparison to qualitative research methods.
Many people feel that using qualitative methods, means your data is not as scientific as experimental methods. However, just like quantitative methods, the validity of the data obtained is checked. Elliott et al. (1995) state the only difference in evaluating these different types of data, is the approach used. Instead of using a statistical analysis to judge the validity of an experiment, Qualitative researchers refer to their colleagues, to judge the credibility and validity of their research.
The primary downfall of qualitative measures is that many meaningful pieces of information obtained can be lost in translation. No matter how hard a researcher tries not to impose their own meaning of data when analysing it, the idea of objectivity in this method is more of an ideal rather than a reality. In order to prevent this Elliott et al. (1999) developed a list of criterion so that the reader is aware of the researcher’s interpretation at all times.
The most common reason to why quantitative measures is deemed more scientific, is because of the use of statistical packages like SPSS to analyse data. But it should be remembered that this is a computerised tool used to understand data and doesn’t have the creative ability to interpret the conclusions drawn. Qualitative measures are able to withstand the effects of outliers (Willig, 2008) as they’re able to theorize and interpret the contradictions found in a data. By paying attention to these anomalies found in results, qualitative methods are able to produce a complete understanding of the phenomenon. Making this type of research, necessary to scientific investigation. After all, if I just told you, I’m giving you a cake, your mind automatically wonders to all the possibilities of the type of cake you would receive. As with this, scientific research should not just simple state whether a study is significant, it should also state why this occurs and qualitative data allows researchers to do so.
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