Experimenter Bias (Definition + Examples)

in the early 1900s a german high school teacher named wilhelm von austen thought that the intelligence of animals was underrated to prove his point he decided to teach his horse hans some basic arithmetics clever hans as the horse came to be known was learning quickly soon he could add subtract multiply and divide and would give correct answers by tapping with his hoof it took scientists more than one year to prove that the horse wasn't doing the calculations himself it turned out that clever hans was simply picking up subtle cues from his owner's facial expressions and gestures influencing the outcome of an experiment in this way is called experimenter bias or observer expectancy bias experimental bias occurs when a researcher either intentionally or unintentionally affects data participants or results in an experiment one of the main causes of the experimenter bias is the human inability to remain completely objective biases like the confirmation bias and hindsight bias affect our judgment every day in the case of the experimenter bias people conducting research may lean toward their original expectations about a hypothesis without the experimenter necessarily being aware of making an error or treating participants differently these expectations can influence the ways in which studies are structured conducted and interpreted they may negatively affect the results making them flawed or irrelevant in a way this is a more specific case of confirmation bias one of the best known examples of experimenter bias is the experiment conducted by psychologists robert rosenthal and kermit fode in 1963 rosenthal and kermit asked two groups of psychology students to assess the ability of rats to navigate a maze while one group was told the rats were bright the other were convinced that they were assigned dull rats in reality the rats were chosen randomly and there was no significant difference between them interestingly the students who were told that their rats were maze bright reported faster running times than the group who was not expecting their rodents to perform well in other words the students expectations directly influenced the obtained results rosenthal and fode's experiment shows how the outcomes of a study can be modified as a consequence of the interaction between the experimenter and the subject but experimenter subject interaction is not the only source of experimenter bias experimenter bias can take place in all study phases from the initial background research and survey design to data analysis and the final presentation of results design bias is one of the most frequent types of experimenter biases it happens when researchers establish a particular hypothesis and shape their entire methodology to confirm it rosenthal showed that 70 percent of experimental biases influence outcomes in favor of the researcher's hypothesis sampling or selection bias refers to choosing participants in a way that certain demographics are underrepresented or overrepresented in a study studies affected by the sampling bias are not based on a fully representative group the omission bias occurs when participants of certain ethnic or age groups are omitted from the sample in the inclusive bias on the contrary samples are selected for convenience such as all participants fitting a narrow demographic range procedural bias arises when the way the experimenter carries out a study affects the results if participants are given only a short time to answer questions for example their responses will be rushed and not show correctly their opinion or knowledge measurement bias is a systematic error that happens during the data collection phase of research it can take place when the equipment used is faulty or when it is not being used correctly interviewer bias is when interviewers consciously or subconsciously influence responses by providing additional information and subtle clues to the subject the subject's response will as we have seen in the rat maze experiment inevitably lean towards the interviewer's own opinions response bias is a tendency to answer questions inaccurately participants may want to provide the answers they think are correct for instance or those that are more socially acceptable than what they truly believe responders are often subject to the hawthorne effect a phenomenon where people make more efforts and perform better in a study because they know they are being observed reporting bias also called selective reporting arises when the dissemination of research findings is influenced by the nature of the results this type of bias is usually out of the researcher's control despite the fact that studies with negative results can be just as significant as positive ones the latter are much more likely to be reported published and cited by others so how can you remove experimenter bias from research unfortunately experimenter bias cannot be fully stamped out as long as humans are involved in the experiment process our upbringings education and experience may always color the way we gather and analyze data but experimenter bias can be controlled first by sharing this phenomenon with people involved in conducting experiments another way to control experimenter bias is to intentionally put together a diverse team and encourage open communication about how to conduct experiments the larger the group the more perspectives will be shared and biases will be revealed biases should be considered at every step of the process most modern experiments are designed in a way to reduce the possibility of biased distorted results in general biases can be kept to a minimum if experimenters are properly trained and clear rules and procedures are put in place for the experiment there are several concrete ways in which researchers can avoid experimenter bias the first way is through a blind analysis wherein all the information which may include the outcome of the experiment is withheld in some cases researchers are not informed about the true results until they have completed the analysis similarly when participants are unaware of the hypothesis they will not be able to influence the outcome of the experiment another method is the double-blind technique which is commonly used in clinical research a double-blind study is done in a way that neither the clinician nor the patients are aware of the nature of treatment they don't know who is receiving an actual treatment and who is given a placebo thus eliminating any design or interview biases from the experiment another good way to limit experimenter bias is to minimize interaction between the respondents and the experimenters the less exposure respondents have to experimenters the less likely it is that they will pick up any cues that would impact their answers one of the common ways to minimize the interaction between participants and experimenters is to pre-record the instructions the last method we'll discuss is peer review which is the evaluation of work by individuals with similar competences as the experimenter their role is to identify potential biases and thus make sure that the study is reliable and worthy of being published so as you can see there are many many different types of biases and although they can cause a lot of trouble in research experimenters have come up with some good ways to limit or remove the effects of their biases that's all for today thanks for watching this video we hope you enjoyed it we really hope you found it helpful and most of all we hope to see you in our next video