An argument is “a connected series of statements intended to establish a proposition.” The connected series of statements are “premises” and the proposition is the conclusion. For example:

  1. All humans are mortal. (premise)
  2. Socrates is a human. (premise)
  3. Therefore, Socrates is mortal. (conclusion)

this example of deductive reasoning which itself is a kind of logical reasoning. there are many other types of reasoning

Reasoning Types

Reasoning Types

Description

Commonsense Reasoning

human reasoning includes:

  • default reasoning
  • preference
  • non-monotonic reasoning
  • abductive reasoning
  • counterfactual reasoning

Logical Reasoning (Deductive - Inductive - Abductive - Analogical - Fallacious)

includes:

  • deductive reasoning
  • inductive reasoning
  • abductive reasoning
  • analogical reasoning

Defeasible Reasoning

defeasible reasoning is a kind of reasoning that is rationally compelling, though not deductively valid. It usually occurs when a rule is given, but there may be specific exceptions to the rule, or subclasses that are subject to a different rule

Fallacious Reasoning

a fallacy is the use of invalid or otherwise faulty reasoning, or “wrong moves” in the construction of an argument. A fallacious argument may be deceptive by appearing to be better than it really is

Differences Between Reasoning Types

The differences between various kinds of reasoning correspond to differences about the conditional (if x then y) that each kind of reasoning uses, and on what premise (or on what authority) the conditional is adopted:

  • Deductive (from meaning postulate or axiom): if p then q (i.e., ¬p v q)
  • Inductive (theory formation; from data, coherence, simplicity, and confirmation): (inducibly) “if p then q”; hence, if p then (deducibly-but-revisably) q
  • Abductive (from data and theory): p and q are correlated, and q is sufficient for p; hence, if p then (abducibly) q as cause
  • Defeasible (from authority): if p then (defeasibly) q
  • Probabilistic (from combinatorics and indifference): if p then (probably) q
  • Statistical (from data and presumption): the frequency of qs among ps is high (or inference from a model fit to data); hence, (in the right context) if p then (probably) q