![]() ![]() ![]() When following an abductive approach, researcher seeks to choose the ‘best’ explanation among many alternative in order to explain ‘surprising facts’ or ‘puzzles’ identified at the start of the research process. ‘Surprising facts’ or ‘puzzles’ may emerge when a researchers encounters with an empirical phenomena that cannot be explained by the existing range of theories. ![]() In abductive approach, the research process starts with ‘surprising facts’ or ‘puzzles’ and the research process is devoted their explanation. The figure below illustrates the main differences between abductive, deductive and inductive reasoning:Īt the same time, it has to be clarified that abductive reasoning is similar to deductive and inductive approaches in a way that it is applied to make logical inferences and construct theories. Abductive reasoning, as a third alternative, overcomes these weaknesses via adopting a pragmatist perspective. Inductive reasoning, on other hand, criticized because “no amount of empirical data will necessarily enable theory-building”. Specifically, deductive reasoning is criticized for the lack of clarity in terms of how to select theory to be tested via formulating hypotheses. The "truth" of a hypothesis lies in its experimental verification and explanatory power.Abductive reasoning, also referred to as abductive approach is set to address weaknesses associated with deductive and inductive approaches. They could be just intuitions or lucky guesses or, as Einstein later called them, "free creations of the human mind." Their origin does not matter (genetic fallacy). Peirce knew that hypotheses need not be arrived at by induction. Newly predicted (discovered) phenomena carry more weight than those originally known. Notice that if the deductions predict phenomena not previously known, the confirmed consequences are not a part of the original phenomena that led to the hypothesis (usually inductively). Experiments then establish the truth or falsity of these consequences. Once the hypothesis is formed, deduction is used to predict other logical consequences. In this case, the scientist makes various guesses (hypotheses) to explain some observations. Peirce identified his abduction with the scientific method of hypothesis-deduction-observation-experiment. But Peirce argued that this kind of reasoning has evolved in humans, who have become adept at selecting the best hypothesis to explain the condition. Strictly speaking, abductive reasoning is fallacious, a logical error. For example, since if it rains, the grass gets wet, one can abduce (hypothesize) that it probably rained. Charles Sanders Peirce called it abduction to infer a premise from a conclusion. If you know all the instances of swans in the pond are white, the conclusion "all swans in this pond are white" is true.Ībduction as a form of reasoning is relatively new. This is a priori probability and is related to enumerative or exhaustive induction. If a jar contains 100 balls, 60 black and 40 white, then the probability of drawing a black ball is. This is the frequentist definition of probability. For example, if all observed swans are white, an inductive conclusion is "all swans are white." Or if two-thirds of observed cows are brown, the probability of another cow being brown is assumed to be two-thirds. Induction draws conclusions which are not certain from multiple examples. Adolphe Quételet Jürgen Renn Juan Roederer Jerome Rothstein David Ruelle Tilman Sauerīiosemiotics Free Will Mental Causation James Symposiumĭeduction is the familar form of syllogistic reasoning in which from true premises one can derive necessarily true conclusions by following the rules of deductive logic. ![]()
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