Quantitative research are normally used to quantify the problem. This is normally by a way of generating numerical data. This is the data, which can be transformed into statistics, which are usable. On the other hand, qualitative research is predominantly exploratory research. It is mainly employed for the purposes of gaining opinions, motivations and underlying reasons. It gives the insight into the problem especially in the development of the ideas and hypothesis for the potential quantitative research (Taylor, 2015).
Biasness exists in both qualitative and quantitative research. Research bias can be defined as a process where the researchers influence the results in order to depict a certain outcome (Maxwell, 2011). Bias distorts the truth. However, it is also inevitable. It is therefore necessary you recognize or be aware of it in order to reduce it. In qualitative research, this affects both the reliability and validity of findings. This in the end affects the final decisions. Five major categories of bias exists in qualitative research, which includes biased answerers, moderator bias, biased reporting, biased questions and biased samples.
Careful analysis of both the systematic and random bias in quantitative research points a very distinct picture. Random biasness usually revolves in limitations in side of the experimenter in the process of data acquisition. The biasness in this instance is mostly minimized by taking more data and an average of the final taken. The systematic biasness on the other hand persists throughout the entire experiment and hence do not result from the experimenter. This biasness are quite difficult to be corrected.
It is evident that the internal validity of a study is greatly influenced by biasness (Maxwell, 2011). They should therefore be eliminated or minimized. Bias minimization is done by applying strategies, which principally exert control over the several factors. These factors must have a relationship between the variables, which are of central interest. Qualitative bias can be minimized through reflexity.
In reflexity, the researchers are supposed to reflect on their personal beliefs and values. These may reduce the instances of inaccuracy in data collection and interpretation. Bias in qualitative research on the other hand can be minimized if you know what to look for and how to manage it. By asking quality questions at the right time and remaining aware and focused on sources of biasness.
