How can scientists decide between competing hypotheses?
As part of the scientific method, scientists are expected to evaluate the validity of their hypothesis. This may encapsulate explanations for possible outliers, anomalous results and describing the variables that may have affected these outcomes. This may be problematic because as much as scientists can try to control/repeat the circumstances of an experiment, an exact replica can never be obtained due to human error or natural changes (such as temperature or wind, if applicable). Therefore, technically, the validity of all data in labs is questionable as it is impossible to reproduce the same situation.
Moreover, according to the principle of simplicity, when deciding between competing theories, scientists generally prefer the simpler one. This mirrors how people tend to have faith in the orderliness of nature, showing not only a subconscious desire to rebuff incomprehensible concepts but also an innate desire to understand the world around us. For instance, Copernicus firmly believed planetary orbits were perfect circles; however, they are actually ellipses, which are arguably less aesthetically pleasing. Thus, ugly truths, however crucial they are, tend to be ignored as they conflict with personal perceptions of beauty. Additionally, as humans enjoy believing that nature makes full sense, if a theory disagrees with previously established knowledge, scientists may be biased toward rejecting this hypothesis. Conclusively, when humans make a discovery or a prediction that is not in line with their pre-existing beliefs, they may choose to side against it.
Scientists may also choose to accept hypotheses that satisfy confirmation bias. This is the notion that people only look for what they want to see, ignoring threatening evidence and considering it an anomaly. An example would be if someone believed all girls preferred wearing skirts over pants. They would take note of every time this was true; however, if they met a girl who said they preferred pants, they would invalidate this piece of data as an exception. Hence, intellectual integrity is a valuable trait in scientists as it is vital to acknowledge evidence that may falsify a hypothesis.