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Experimenter's Bias: Definition, Examples and Effects

Experimenter's bias, also known as experimenter effect, is a phenomenon in which the researcher’s expectations, beliefs, or values influence the results of an experiment. This bias can be intentional or unintentional, and can lead to inaccurate results. It is important to be aware of this bias and take steps to minimize its effects.


Definition: Experimenter's bias is a phenomenon in which the researcher’s expectations, beliefs, or values influence the results of an experiment. This bias can be intentional or unintentional, and can lead to inaccurate results.


Examples: One example of experimenter's bias is when a researcher has a preconceived notion of the outcome of an experiment and then designs the experiment in a way that will produce the desired result. Another example is when a researcher is aware of the results of an experiment before it is conducted and then interprets the results in a way that supports their own beliefs.


Effects: Experimenter's bias can lead to inaccurate results and can undermine the validity of an experiment. It can also lead to a lack of objectivity in the interpretation of results, which can lead to incorrect conclusions. Additionally, it can lead to a lack of trust in the research process, as well as a lack of confidence in the results.


Overall, experimenter's bias is an important phenomenon to be aware of and to take steps to minimize. By understanding the potential for bias and taking steps to reduce it, researchers can ensure that their experiments are conducted in an unbiased and accurate manner.


Do you want to expand your knowledge on this topic? Read our full in-depth article on cognitive biases.


Do you have extra 15 minutes today? Takeour fun and interactive quiz to learn which of 16 reasoning styles you use, your overall level of rationality, and what you can do now to improve your rationality skills.

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