Experimenters bias is a research phenomenon where in a researcher or an experimenter’s resolution is biased. Read more.
Robert Rosenthal, a renowned psychologist was among the first one’s to exhibit experimenters bias as ‘experimenter expectancies’. This had not caught a lot attention till the early 1960s.
What is Experimenter Bias?
The term experimenter bias is related to the researcher’s influence on the outcome of his research. When researchers choose their topic of research there is a probable outcome that they have predicted in their minds. In psychology this is termed as ‘observer-expectancy effect’. Because of the prediction of the outcome in advance, the research methodology or the way the outcome is analyzed or even the way it is interpreted can be influenced. This basically comes to the point where researches that have been taken up with the influence of a probable result in mind, will not derive a precise result. This makes the research unreliable. The judgment or the conclusion is deviated form what the actual outcome should be.
Experimenter bias can occur in any facet of a research. Researchers bias can influence their literature review, the study sample they have taken, also the method of analyzing the data, and even in representing the outcome of the research.
Qualitative Research Bias
Usually a qualitative research bias is found in social science researches. This is because it is not as accurate as physical science. Social science, studies more of behavioral patterns, and measuring a behavior or even quantifying it is not possible. The way qualitative methods are used are also different. Hence, results of a social study research will be based on what the researcher’s interpretation is. Experimenter bias in social behavioral studies is sometimes ineluctable. Like in the case of economics, a study by a Marxist’s view on a capitalism and Keynesian’s perspective of mixed economy, both will have biased interpretations of the outcome of the same research. In case of physical science also, the outcomes can be biased. This happens when researchers round up a figure, making the conclusion inaccurate.
Quantitative Research Bias
Quantitative bias is associated with choosing a wrong sample or a wrong way of analysis. A wrong sample would be a biased sample. Let’s say you are trying to research on a company’s work policies, but for the review you take a survey of only the women at work and not the men. In this case, the sample is biased as it does not show men’s opinion. Also, if a sample is small then, again the research’s outcome would be biased. Even choosing a wrong or an inaccurate way of data analysis could lead to a quantitative bias.
How to Avoid Experimenter Bias?
Experimenter bias is a human incompetency of being objective and inciting towards subjectivity.
Double-Blind Design
This is the most common and efficient technique used by researchers. Here the researchers are to be kept aloof from what the research participants outcome could be. Also, the research participants are not allowed to interact with the researcher to know what his perspective on the research is.
Mechanize Procedures
Nothing is as magnificent as a human brain therefore to avoid the complexities a brain goes through, it is best to mechanize your research procedures. Use a computer to store and manage data and use analytical software to analyze data. A computer will not give you a biased answer, it will mathematically solve whatever is put before it.
Research Protocols
A recommended format for a research protocol should be adhered to by the students. This makes the research systematic and will reduce the scope of being biased. The researcher will have to stepwise follow the protocol and that will prevent them from jumping to a conclusion or a research methodology directly.
Investigator Intervention
An investigator should plan the research for the researcher instead of the entire liberty lying in the hands of the experimenter. The researcher should be told what to do and what not to do.
Consider More Aspects
While looking out at the conclusion, not only the cause and effect of independent and dependent variables should be considered but also what effect does it have on other indirectly related variables should be mentioned.
Experimenters are bound to maneuver their research according to what their interpretation and understanding is for the subject. Though when the research investigators are mentoring and tracking the researchers movements, intensity of the prejudice can be reduced.