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Elimination most of the biases in research

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Elimination most of the biases in research

One of the researcher’s biggest nightmares is validity and reliability issues. Bias is one of the factors that can result in validity and reliability issues in research. There are different types of bias, which include the researcher or interviewer bias. Interviewer bias is hard to identify, especially for novice researchers like me. Nevertheless, according to it is impossible to have research that has no bias. The researcher’s option is to reduce bias and limit the effects of the bias on the data collected. In this essay, I reflect on potential biases identified during my case study and strategies that I used to address the biases and limit the adverse effects.

Research has shown that social media has numerous benefits for businesses. However, researchers have lamented that there is a knowledge gap concerning the use of social media in small business. Research has also shown that small business owners have not adopted social media and are thus missing out on the benefits of social media partly because they are unaware of the benefits of social media in business. Therefore, my research topic was the use of social media in business while the research problem is that small business owners have not adopted the use of social media because they either do not know how to use it or do not know the benefits

Bias is defined as anything that can distort the findings of a study. One of the biases in my case study was interviewer bias. Interviewer bias results from comments, tones, behavior that influences the answers interviewees give. At first, when formulating the questions, I assumed that I knew most of the information there was to gather about the use of social media because I have used social media more than once to purchase items I needed. Luckily I had a colleague of mine interview me using the interview protocol I had formulated and recorded the interview. Later, when I listened to the interview, I identified various questions that needed clarification and follow up. If I had not done so, it would have resorted to measurement bias. Moreover, I realized that some questions were leading, which could have limited the response given by the interviews. Therefore, I adopted a strategy of formulating open-ended questions to ensure that I did not indolence the answers given by respondents.

One other strategy that I used to prevent bias was the use of cultural reflexivity. One of the ways to use cultural reflexivity is to familiarize oneself with surroundings before the interview and to conduct an interview in the environment of the case being studied. I visited my respondents and familiarized myself with them in a bid to gain their trust and observe how social media us used in their business. Therefore, visiting them before the interview helped me have a rapport with the interviewees, and thus they were willing to speak to me during the interview, which helped measurement bias that can also arise when interviewees refuse to respond to questions.

While I was able to eliminate most of the biases in my research, I was not able to eliminate all the biases. My case study had a selection bias. Selection bias occurs when the sample is not representative of the entire population. Due to time and resource constraints, I used only two participates in my case study. The number of participants in my study was not representative of the small business owners population in the US.

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