I think there are several reasons why reliability is important, not only in the real world but also in statistics, before I go into more depth, first I need to define the term reliability – it refers to which a measure is stable or consistent and produces similar results when administered repeatedly, behaviour is one of the many examples of a measure.
I will address the reasons in terms of quantitative and qualitative data. While for qualitative results, reliability is elected through the use of statistics, such as the SD; for quantitative results, reliability can be consistent in subsequent tests. I do not think that reliability is appropriate and does not play an important role in conducting qualitative studies, as these kind of studies focusing on the value and interpretations of experience by the participant. This can be backed up by Caroline Stenbacka, obligated by the complexion of qualitative studies, rather than explaining human experience, they aim at understanding it, which make the reliability of qualitative research difficult to assess.
However on the other hand, for researchers, whether the same measurement process yields the same results is a rather important aim, as this proves and assure them how their results can be as consistent and stable, and can be replicated in the future by others. Poor reliability degrades the precision of measurement and reduces researchers’ ability to keep track on the changes in measurements in studies, and this is why it is important to have reliable results. For example, when carrying out a study that might possibly lead to a theory, however this can be rejected or criticised due to the different inconsistent results that were shown under the same procedure. For Freud’ study, his “Little Hans” case study cannot be reliable if the study was repeated, there is no guarantee that same results could be done under the same condition, however the enrich data could be useful, hence Freud is a well know psychologist even in the 21st century. At this point, I do not think that reliability is that important as it turns out to be in the sense of qualitative data.
In conclusion, Stenbacka (2001) has suggested that “… a good quality research when reliability is a concept to evaluate quality in quantitative study with a purpose of explaining while quality concept in qualitative study has the purpose of generating understanding …”. This makes me think that the use of reliability has now becoming onto an even more important, and leading role in terms of quantitative results, this has never really strikes me until now. Once people know how reliable research is, it can be helpful for further development of future research, it is also applicable to the real world and can be used widely in different fields, such as educations.