Educational objectives The aims is to provide students with tools to apply what they have studied in their curricula courses. Stages and seminars attending will be recognized.
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Educational objectives Learning goals.
Practical exercises to becarried out in a computer room of the problems in the financial sector covered in the lessons of the financial mathematic, in particular the calculation of the internal rate of return and measuring the term structure of interest rates.
Knowledge and understanding.
Ability to implement algorithms for solving problems in the financial sector covered in the course of financial mathematic.
Applying knowledge and understanding.
Software implementation of theoretical subjects.
Making judgements.
Critical tools for the evaluation of literature of the field.
Communication skills.
Skill to explain software output.
Learning skills.
Manage data typical of Financial Mathematics.
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Educational objectives Learning goals.
Students must acquire the ability of solving inferential problems using both analityc and computational (using the software R) skills.
Knowledge and understanding Knowledge and understanding of frequentist methods for: point and interva estimation, testing. Use of the software R.
Applying knowledge and understanding.
Ability in solving inferential problems/exercises for a wide range of parametric models and to use the software R to study properties of inferential methods.
Making judgements.
Students acquire ability in making judgements by:
- applying inferential methods to different models
- comparing alternative methods
- using the methods on real data and interpreting the results.
Communication skills.
Communication skills are acquired by using the specific scientific lexicon/language in written and oral exams.
Learning skills.
The course provide students with fundamental learning skills necessary to approach more advances classes in Statistics.
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Educational objectives Learning goals
The primary aim of the course is to make students learn the main aspects of real analysis
related to the study of probability theory. At the end of the course, students are able to
solve analytical problems through the application of such theoretical concepts.
Furthermore, the mathematical methods discussed during the classes represent tools for
the study of stochastic processes.
Knowledge and understanding.
At the end of the course, students know the main aspects of real analysis and probability
theory that are useful for the study of stochastic processes.
Applying knowledge and understanding.
At the end of the course students know how to formalize problems subject to and
characterized by deterministic and/or random complex mathematical frameworks, how to
choose the appropriate methods to solve them.
Making judgements.
Students develop critical thinking by applying the relevant theory to a wide range of real-
world problems that can be described by applying the mathematical methods models
discussed during the course. They also develop critical judgement attitudes by comparing
alternative solutions to the same problem using different methodological approaches.
Communication skills.
Students, through the study and the development of exercises, are expected to acquire an
appropriate technical-scientific language, which is evaluated in the final written tests, as
well as in the oral exams.
Learning skills.
At the end of the course, the students know the basic concepts of real analysis and
probability theory that allow them to attend the course which entails stochastic processes.
They are also able to apply probabilistic methods to theoretical and experimental
problems from the physical, natural, economic and social sciences.
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