Define auxiliary hypothesis by Michelle Piazza - issuu
A fairly standard reply to this line of argument is to suggest thatwhat Laudan and Leplin really show is that the notion of empiricalequivalence must be applied to larger collections of beliefs thanthose traditionally identified as scientific theories—at leastlarge enough to encompass the auxiliary assumptions needed to deriveempirical predictions from them. At the extreme, perhaps this meansthat the notion of empirical equivalents (or at least timelessempirical equivalents) cannot be applied to anything less than“systems of the world” (i.e. total Quinean webs ofbelief), but even that is not fatal: what the champion of contrastiveunderdetermination asserts is that there are empirically equivalentsystems of the world that incorporate different theories ofthe nature of light, or spacetime, or whatever. On the other hand, itmight seem that quick examples like van Fraassen’s variants ofNewtonian cosmology do not serve to make this thesis asplausible as the more limited claim of empirical equivalence forindividual theories. It seems equally natural, however, to respond toLaudan and Leplin simply by conceding the variability in empiricalequivalence but insisting that this is not enough to undermine theproblem. Empirical equivalents create a serious obstacle to belief ina theory so long as there is some empirical equivalent tothat theory at any given time, but it need not be the same one at eachtime. On this line of thinking, cases like van Fraassen’sNewtonian example illustrate how easy it is for theories to admit ofempirical equivalents at any given time, and thus constitute a reasonfor thinking that there probably are or will be empirical equivalentsto any given theory at any particular time we consider it, assuringthat whenever the question of belief in a given theory arises, thechallenge posed to it by constrastive underdetermination arises aswell.
Auxiliary hypothesis example - Leipzig Reisemobilhafen
What Is An Auxiliary Hypothesis
"One of the reasons for this state of affairs is the fact that the Efficient Markets Hypothesis, by itself, is not a well-defined and empirically refutable hypothesis. To make it operational, one must specify additional structure, e.g., investor’ preferences, information structure, business conditions, etc. But then a test of the Efficient Markets Hypothesis becomes a test of several auxiliary hypotheses as well, and a rejection of such a joint hypothesis tells us little about which aspect of the joint hypothesis is inconsistent with the data. Are stock prices too volatile because markets are inefficient, or is it due to risk aversion, or dividend smoothing? All three inferences are consistent with the data. Moreover, new statistical tests designed to distinguish among them will no doubt require auxiliary hypotheses of their own which, in turn, may be questioned."
Lo and MacKinlay (1999), pages 6-7
Efficient Markets Hypothesis: Joint Hypothesis
The alternative hypothesis is what we are attempting to demonstrate in an indirect way by the use of our hypothesis test. If the null hypothesis is rejected, then we accept the alternative hypothesis. If the null hypothesis is not rejected, then we do not accept the alternative hypothesis. Going back to the above example of mean human body temperature, the alternative hypothesis is “The average adult human body temperature is not 98.6 degrees Fahrenheit.”