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Part I. Foundations of Probability:
1. Necessary and sufficient conditions for existence of a unique measure strictly agreeing with a qualititative probability ordering;
2. Necessary and sufficient qualitative axioms for conditional probability;
3. On using random relations to generate upper and lower probabilities;
4. Conditions on upper and lower probabilities to imply probabilities;
5. Qualitative axioms for random-variable representation of extensive quantifiers;
Part II. Causality and Quantum Mechanics:
6. Stochastic incompleteness of quantum mechanics;
7. On the determinism of hidden variable theories with strict correlation and conditional statistical independence of observables;
8. A new proof of the impossibility of hidden variables using the principles of exchangeability and identity of conditional distribution;
9. When are probabilistic explanations possible?;
10. Causality and symmetry;
11. New Bell-type inequalities for N>4 necessary for existence of a hidden variable;
12. Existence of hidden variables having only upper probabilities;
Part III. Applications in Education:
13. Mastery learning of elementary mathematics: theory and data.
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