Affine properties are more general than metric ones because they are independent of the choice of a coordinate system. Nevertheless, a metric, that is to say, a scalar product which takes each pair of vectors and returns a real number, is meaningful when n vectors, which are all unit vectorsand orthogonal to each other, constitute a basis for the n-dimensional vector space A. In such a space n events E i , i = 1,...,n, whose Cartesian coordinates turn out to be x i , are represented in a linear form. A metric is also meaningful when we transfer on a straight line the n-dimensional structure of A into which the constituents of the partition determined by E 1 ,...,E n are visualized. The dot product of two vectors of the n- dimensional real space R n is invariant: of these two vectors the former represents the possible values for a given random quantity, while the latter represents the corresponding probabilities which are assigned to them in a subjective fashion. We deduce these original results, which are the foundation of our next and extensive study concerning the formulation of a geometric, well-organized and original theory of random quantities, from pioneering works which deal with a specific geometric interpretation of probability concept, unlike the most part of the current ones which are pleased to keep the real and deep meaning of probability notion a secret because they consider a success to give a uniquely determined answer to a problem even when it is indeterminate. Therefore, we believe that it is inevitable that our references limit themselves to these pioneering works.

### Subjective Probability and Geometry: Three Metric Theorems Concerning Random Quantities

#### Abstract

Affine properties are more general than metric ones because they are independent of the choice of a coordinate system. Nevertheless, a metric, that is to say, a scalar product which takes each pair of vectors and returns a real number, is meaningful when n vectors, which are all unit vectorsand orthogonal to each other, constitute a basis for the n-dimensional vector space A. In such a space n events E i , i = 1,...,n, whose Cartesian coordinates turn out to be x i , are represented in a linear form. A metric is also meaningful when we transfer on a straight line the n-dimensional structure of A into which the constituents of the partition determined by E 1 ,...,E n are visualized. The dot product of two vectors of the n- dimensional real space R n is invariant: of these two vectors the former represents the possible values for a given random quantity, while the latter represents the corresponding probabilities which are assigned to them in a subjective fashion. We deduce these original results, which are the foundation of our next and extensive study concerning the formulation of a geometric, well-organized and original theory of random quantities, from pioneering works which deal with a specific geometric interpretation of probability concept, unlike the most part of the current ones which are pleased to keep the real and deep meaning of probability notion a secret because they consider a success to give a uniquely determined answer to a problem even when it is indeterminate. Therefore, we believe that it is inevitable that our references limit themselves to these pioneering works.
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Utilizza questo identificativo per citare o creare un link a questo documento: `https://hdl.handle.net/11564/689256`
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