Philosophy Dictionary of Arguments

Home Screenshot Tabelle Begriffe

 
Monotony: Monotony in mathematics refers to the behavior of a function as its input changes. A function is said to be monotonic if its output either always increases or always decreases as its input increases. See also Functions.
_____________
Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments.

 
Author Concept Summary/Quotes Sources

Gerhard Schurz on Monotony - Dictionary of Arguments

I 55
Def Monotony/Schurz: A valid conclusion from premises P1...Pn to the conclusion K is called monotonic, gdw. if it remains valid even after adding arbitrary further premises. (New information does not change anything.
All deductive inferences are monotonic, i.e. they satisfy the monotonicity rule: P1,..,Pn/K is valid >for any Q/P1...Pn/K is valid.
>Validity
, >Conclusions, >Logic, >Inference.
Uncertain inferences: are not monotone.
Notation: monotone inferences: "/"
Non-monotonic: "II".
Non-monotonic inferences: Here we are not talking about validity but correctness. A correct non-monotonic inference can become incorrect by new information. Even if the truth of the previous premises is not affected. A black swan does not make the previous observations of white swans wrong. So it always has only provisional validity.
Non-monotonicity/probability theory: The probabilistic reason of non-monotonicity is: From the fact that the conditional probability of A under the assumption ("premise") B is high, it does not always follow that also the probability of A under the assumption of B plus a further assumption C is high.
>Conditional probability, >Probability, >Bayesianism.

I 154
Non-monotonic/single case probability/statistical/Schurz difference to strict (non-statistical) hypotheses: (when explaining single cases):
Non-statistical: the conclusion Ka of a deductive inference with true premises (x)(Ax > Kx) and Aa may be split off at any time.
I 155
One may infer the truth of the conclusion from the truth of the premises without knowing what else is true.
Against:
statistich: Bsp from the premise p(Kx I Ax) = 90 % and Aa, however, one may conclude Ga with subjective belief probability of 0.9 only if the condition of the closest reference class is guaranteed. The antecedent information A must include all statistically relevant information about a.
>Hypotheses, >Probability, >Probability theory, >Verification, >Relevance.

_____________
Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments
The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.

Schu I
G. Schurz
Einführung in die Wissenschaftstheorie Darmstadt 2006


Send Link
> Counter arguments against Schurz
> Counter arguments in relation to Monotony

Authors A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   Y   Z  


Concepts A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   Z  



Ed. Martin Schulz, access date 2024-04-19
Legal Notice   Contact   Data protection declaration