A hypothesis is a suggested explanation of a phenomenon or reasoned proposal suggesting a possible correlation between multiple phenomena. The term is derived from the ancient Greek, hypotithenai meaning "to put under" or "to suppose." A scientific hypothesis must be testable and generally will be based upon previous observations or extensions of scientific theories.
In common usage at present, a hypothesis refers to a provisional idea whose merit needs evaluation. To be evaluated, the specifics of the hypothesis need to be defined in operational terms. A hypothesis requires more work by the researcher in order to either confirm or disprove it. In due course, a confirmed hypothesis may become part of a theory or occasionally may grow to become a theory itself. Normally, scientific hypotheses have the form of a mathematical model. Sometimes, but not always, they can also be formulated as existential statements, stating that some particular instance of the phenomenon being studied has some characteristic and causal explanations, which have the general form of universal statements, stating that every instance of the phenomenon has a particular characteristic.
Any useful hypothesis will enable predictions, by reasoning including deductive reasoning. It might predict the outcome of an experiment in a laboratory setting or the observation of a phenomenon in nature. The prediction can also be statistical and only talk about probabilities. Karl Popper, following others, has argued that a hypothesis must be falsifiable, and that a proposition or theory cannot be called scientific if it does not admit the possibility of being shown false. By this additional criterion, it must at least in principle be possible to make an observation that would show the proposition to be false, even if that observation had not actually been made. A falsifiable hypothesis can greatly simplify the process of testing to determine whether the hypothesis has instances in which it is false.
It is essential that the outcome be currently unknown or reasonably under continuing investigation. Only in this case does the experiment, test or study potentially increase the probability that the hypothesis be true. If the outcome is already known, it is called a consequence and should have already been considered while formulating the hypothesis. If the predictions are not accessible by observation or experience, the hypothesis is not yet useful, and must wait for others who might come afterward to make possible the needed observations. For example, a new technology or theory might make the necessary experiments feasible.
A hypothesis about possible correlation does not stipulate the cause and effect per se, only stating that 'A is related to B'. Causal relationships can be more difficult to verify than correlations, because quite commonly intervening variables are also involved which may give rise to the appearance of a possibly direct cause and effect relationship, but which upon further investigation turn out to be more directly caused by some other factor than what is stated in the proposition. Also, a mere observation of a change in one variable, when correlated with a change in another variable, can actually mistake the effect for the cause, and vice-versa (i.e., potentially get the hypothesized cause and effect backwards).
Empirical hypotheses that have been repeatedly verified may become sufficiently dependable that, at some point in time, they become considered to be "proven" and are then termed laws. Alternately, such repeatedly verified hypotheses may instead be referred to simply as "adequately verified," or "dependable."
As an example: someone who enters a new country and observes only white sheep might form the hypothesis that all sheep in that country are white. It can be considered a hypothesis, as it is falsifiable. Anyone could falsify the hypothesis by observing a single black sheep. Provided that the experimental uncertainties are small (for example, provided that one can fairly reliably distinguish the observed black sheep from (say) a goat), and provided that the experimenter has correctly interpreted the statement of the hypothesis (for example, does the meaning of "sheep" include rams?), finding a black sheep falsifies the "white sheep only" hypothesis. This is probably the easiest way to understand the term "hypothesis".
According to Schick and Vaughn (2002), researchers weighing up alternative hypotheses may take into consideration:
Isaac Newton, Principia Mathematica. A New Translation by I. Bernard Cohen and Anne Whitman, translators. University of California Press 1999 ISBN 0-520-08817-4
Letter to Eduard Study from Albert Einstein, September 25,1918 Collected Papers of Albert Einstein, J.J. Stachel and Robert Schulmann, eds. Princeton University Press 1987If you get a deffenition you what the word is.
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