Explanatory Role of Probability in Philosophy and Science

General data

Course ID:	3501-ERP18-M-OG
Erasmus code / ISCED:	08.1 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0223) Philosophy and ethics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Explanatory Role of Probability in Philosophy and Science
Name in Polish:	Eksplanacyjna rola prawdopodobieństwa w filozofii i w nauce
Organizational unit:	Institute of Philosophy
Course groups:	General university courses General university courses in the humanities
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	elective monographs
Prerequisites (description):	(in Polish) Zaliczenie kursu logiki może być pomocne, lecz nie jest obowiązkowe
Mode:	Classroom
Short description:	Probability theory is at present a formal theory. But for the reason of different roles which probability plays, the notion of probability is interpreted in different ways. For example, is interpreted as an objective property of the world, and as an degree of belief. This lecture is devoted to the explication of these two fundamental interpretations of probability illustrated by examples of philosophical theories as objective and subjective Bayesianism and confirmation theory, as well as scientific theories such as statistical and quantum mechanics.
Full description:	Here is an agenda of the lecture: 1. The standard probability theory established by Kolmogorov a. probability space b. probability as a real function c. probability as a measure d. probability as the Lebegue measure e. consequences which the theorem about the existence of unmeasurable sets has for the standard probability theory f. axioms of the standard probability theory g. discussion over the axiom of countable additivity 2. The fundamental interpretations of probability: objective interpretation a. probability as relative frequency b. probability as propensity c. the notion of deviation d. explanatory role of probability in empirical theories such as statistical mechanics and quantum mechanics e. ontic and epistemic determinism 3. The fundamental interpretations of probability: subjective interpretation a. discussion over representing degrees of belief by probabilities b. representation of beliefs by families of probability functions c. probabilities as the result of applying Bayesian norms d. explanatory role of probability in inductive logics e. explanatory role of probability in probabilistic logics
Bibliography:	Krystyna Simons, "Paradoksy prawdopodobieństwa", 2017, Warszawa: PWN. Inne pozycje bibliograficzne zostaną podane w czasie wykładu.
Learning outcomes:	Concerning the student’s knowledge Student knows which are theoretical foundations of probability; Student knows which is the actual stage of research over the role of probability in philosophy and science; Student knows which are the main problems concerning the representation of beliefs in the standard probability theory; Student knows which are proposed in the literature solutions of the problems representing beliefs in the standard probability theory and which problems are still open; Student knows which are problems with applying probability in statistical mechanics and in quantum mechanics. Concerning the student’s accomplishments Student can formulate problems in the area confined by the subject of this lecture; Student can apply formal tools and techniques for the analysis of questions confined by the subject of this lecture; Student can prepare an essay, MA or PhD dissertation on the subject of this lecture. Concerning social competences Student can make use of the knowledge acquired during this lecture; Student can defend his view making use of the notion introduced during this lecture; Student can take part in discussion on the explanatory role of probability in philosophy and science.
Assessment methods and assessment criteria:	Student is evaluated for his (her) presence on these lectures, as well as for his (her) conversation with the lecturer on the topics explained during this course.

This course is not currently offered.

Course descriptions are protected by copyright.
Copyright by University of Warsaw.