We believe: Hypothesis 1.2: More variety of data will reduce information asymmetry.
Suppose evidence e gives you justification for believing hypothesis or proposition p and you know that p entails another proposition q that you have not directly checked.
Even if evidence E is sufficient to justify believing hypothesis H when considered in isolation, it does not follow that one who possesses evidence E is justified in believing H on its basis.
Some topics she has written on include distributive justice; the relationship between assigning probability to a hypothesis and believing that hypothesis outright; the conditions under which one ought to stop looking for more evidence and make a decision; and the nature of faith, both in the religious and the more mundane sense.
Alan Musgrave has astutely remarked that even if we agree that the fact that a theory has so far survived severe tests does not provide a reason for the hypothesis, nevertheless it does provide a reason for believing the hypothesis (Musgrave 1974).
The key characteristic of Bayesian statistics flows directly from the epistemic interpretation: under this interpretation it becomes possible to assign probability to a statistical hypothesis and to relate this probability, understood as an expression of how strongly we believe the hypothesis, to the probabilities of events.
If we choose to believe his hypothesis, we open ourselves to a life forever full of the possibility of greater satisfaction, regardless of whether the final product is one of genius.
So by an underdetermination-style argument, one is not justified in believing either hypothesis.
"We believe this hypothesis has not received an adequate test," he says.
