Questions below pertain to the following passage: How are Hypotheses Confirmed? Most scientists agree that while the scientific method is an invaluable methodological tool, it is not a perfect method for arriving at objectively true universals. For example, a scientist may be interested in demonstrating that all members of a given category x are also members of a given category y. However, a hypothesis of the form 'all x are also y' cannot be proven true by observing instances of x and demonstrating that they are also y. Even if one were able to observe all instances of x in the universe... Show more

Questions below pertain to the following passage:

How are Hypotheses Confirmed?
Most scientists agree that while the scientific method is an invaluable methodological tool, it is not a perfect method for arriving at objectively true universals. For example, a scientist may be interested in demonstrating that all members of a given category x are also members of a given category y. However, a hypothesis of the form 'all x are also y' cannot be proven true by observing instances of x and demonstrating that they are also y. Even if one were able to observe all instances of x in the universe and demonstrate that each one was also y, this still falls short of proving the hypothesis all x are y, because it is still possible that at some point in the past, there existed an x that was not y, or that at some point in the future, there will exist an x that is not y.

Leaving that issue aside, though, consider the impact on the hypothesis of two separate pieces of data: 1) an x that is y; 2) an x that is not y. The first is just one of many pieces of data that must be assembled in order to give weight to the hypothesis. The second is a single piece of data that independently invalidates the hypothesis. The problem, though, is not with the evidence or with reality, but with the way we have chosen to approach the issue.

As an alternative to this true/false paradigm, we can instead choose to form our hypotheses in such a way that we are not seeking to make universal claims of fact but instead are seeking to make probabilistic claims of likelihood. Consider the difference between 'all x are also y' and 'a given x is also y.' The answer to the first must be universally yes or universally no. The answer to the second is a percentage based on probability. Before going further, we will assign example parameters to the terms x and y. Consider instead the two hypotheses: 1) all monkeys have hair; 2) a given monkey will have hair. With our first hypothesis, as we have already seen, we would have to investigate every monkey in existence in our attempt to prove the hypothesis. A single instance of a hairless monkey would invalidate the hypothesis. With the second hypothesis, however, we can investigate a representative sample of monkeys and make an estimate of the probability of hair within the population (all monkeys) based on the results. This approach does two things for us. First, it allows us to make a prediction about any given monkey without checking the entire population. Second, it allows us to keep making this prediction even if a hairless monkey is found, because we are only stating the likelihood of a monkey having hair, rather than making a universal claim.

The fact that a hairless monkey could one day be discovered does not invalidate Hypothesis 2 as it would Hypothesis 1. Rather, it is expected that there may be rare “disconfirming” occurrences since the hypothesis is only stated as a likelihood rather than a certainty. Because of the impossibility of stating with certainty that a certain event has never happened, does not currently exist, and never will exist, scientific hypotheses are frequently confirmed as probabilities rather than universal truths.

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