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Reasoning about causes, effects and rules requires different approaches given what we know and don't know.
In logical reasoning, we usually deal with causes (= premises or preconditions) and effects (= conclusions or consequences) as well as rules that govern the relationship between cause and effect.
In the real world, we usually observe either causes or effects or we know of certain rules that should produce effects given a cause — and we try to find out about the missing part.
For example, the goal of medical diagnosis is to find the cause for observed symptoms (effects), while applying a vast body of knowledge about diseases and biology (rules).
The cause is abduced, given the rule and an effect.
In economic forecasting, however, one tries to make a prediction about the future growth of the economy (effect) given observations about economic activity today (cause) and theories about how the economic system and its relationships (rule).
The (potential) effect is deduced from the rule and the cause.
In yet another situation, you might observe that many birds are coming to your local lake (effect) whenever it is summer (cause). This can lead to you to conclude that summer makes birds come to lakes (rule).
Given the cause and the effect, the rule is induced.
The above are examples of three different main forms of logical reasoning (= main forms of inference), applied depending on what we observe and what we want to know.
Given an effect we observe and a rule we know would produce the effect, we reason towards understanding what might have caused the effect.
Abduction is used in medical diagnosis (see example above), and in both scientific research and business management to generate hypotheses about which causes are present hat lead to the observed effect.
Abductive arguments never guarantee their conclusions (about the cause), as there could be other causes producing the same effect. However, good abductive arguments give us very good reasons to believe their conclusions.
This sort of inference is called inference to the best explanation.
Deductive reasoning goes from the general (theory) to the specific (observation). Given a true rule, a good deductive argument guarantees that an effect will be true if we observe a cause. In other words, if the rule between cause and effect is true and a cause is correctly identified, the effect has to follow necessarily.
Deduction is used to test hypothesis in scientific research and other fields, as well as make predictions about outcomes.
In reality, rules are often uncertain (hypotheses and theories) or causes are not specified or understood accurately.
Inductive reasoning goes from the specific to the general. Given observations about causes and effects, patterns, models and generalizations (rules) that are in line with the observed are generated.
Induction generates hypotheses about the relationship between observations and is used in scientific research (together with both Abduction and Deduction) as well as in our personal lives when we try to figure out why, for example, people behave a certain way.
Like with Abduction, and opposed to Deduction, Induction can never guarantee that our induced result is correct — it can only make argument highly probable.
“All opinions are not equal. Some are a very great deal more robust, sophisticated and well supported in logic and argument than others.”
— Douglas Adams
“The decay of Logic results from an untroubled assumption that the particular is real and the universal is not.”
— C.S. Lewis
➞ This animated video explains the nature, application and importance of abductive reasoning perfectly.
➞ This video explains the deductive reasoning in a similar way.
➞ A great overview of all three modes of reasoning can be found in this 4-min. explanation.
➞ For a deep dive into logical reasoning and the vast landscape of constructing arguments and building consistent chains of thought, explore this Wikipedia article and follow its trails.
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