Personal bias is unavoidable in research. It may be in the form of selectivity of materials, methods, tools, time, place, season, mood, uniformity of sampling and many other things.
Are there any statistical or any other corrective tools to avoid individual bias, if any, on the part of researcher both for lab and field experiments?
A widely used method in scientific experiments which may reduce bias satisfactorily, if applied properly, is randomization.
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A widely used method in scientific experiments which may reduce bias satisfactorily, if applied properly, is randomization.
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In addition, a reduction of bias in experiments with plants may be achieved by their rotation on a regular basis.
To minimize human bias try to go with an open mind and not be committed to any hypotheses although one must start with a hypothesis for any research project. If you are conducting a design of experiments especially in the physical sciences or engineering make sure that you randomize the run order using a random number generator. If it is a survey or ethnographic type of research try to make them blind studies as much as possible. Also ask someone else to code each run or data point so that bias can be minimized. If judges are going to rate an outcome make sure that the judges are trained properly as well as randomizing the order in which the judges are going to rate as well as rotating the judges.
In addition, a reduction of bias in experiments with plants may be achieved by their rotation on a regular basis.
Also, sampling bias (bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others) may be statistically corrected more or less satisfactorily depending on the selection model chosen (https://en.wikipedia.org/wiki/Sampling_bias).
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