20410338 - CP210 - Introduction to Probability

Elementary probability theory: discrete distributions, repeated trials, continuous random variables. Some basic limit theorems and introduction to Markov chains.

Curriculum

teacher profile | teaching materials

Programme

1. Introduction to combinatorial analysis.

2. Introduction to Probability.

3. Conditional probability, Bayes' formula. Independence.

4. Discrete random variables. Bernoulli, binomials, Poisson, geometric, hipergeometric, negative binomial.
Expected value.

5. Continuous random varaibles. Uniform, exponential, gamma, gaussian.
Expected value.

6. Independent variables and joint laws.
Sum of two or more independent random variables. Poisson process. Maxima and minima of independent random variables.

7. Limit theorems. Markov and Chebyshev inequalities.Weak law of large numbers. Generating functions and a sketch of proof of the central limit theorem.


Core Documentation

Sheldon M. Ross, Calcolo delle Probabilita'. Apogeo, (2007).



F. Caravenna, P. Dai Pra, Probabilita'. Springer, (2013).

Reference Bibliography

Sheldon M. Ross, Calcolo delle Probabilita'. Apogeo, (2007). F. Caravenna, P. Dai Pra, Probabilita'. Springer, (2013).

Type of delivery of the course

Lecture, exercise sessions, written solutions available online.

Type of evaluation

2 intermediate written examinations (2 hours each) and 1 written final examination (3 hours).

teacher profile | teaching materials

Programme

Refer to the web-page of the course

Core Documentation

Sheldon M. Ross, Calcolo delle probabilita' (Apogeo Ed.)
F. Caravenna e P. Dai Pra, Probabilita' (Springer Ed.)

Reference Bibliography

Sheldon M. Ross, Calcolo delle probabilita' (Apogeo Ed.) F. Caravenna e P. Dai Pra, Probabilita' (Springer Ed.)

Type of delivery of the course

Exercises are solved on the blackboard - the proposed exercises aim at clarifying and practicing with the concepts seen during the lectures

Type of evaluation

Refer to the web-page of the course

teacher profile | teaching materials

Programme

1. Introduction to combinatorial analysis.

2. Introduction to Probability.

3. Conditional probability, Bayes' formula. Independence.

4. Discrete random variables. Bernoulli, binomials, Poisson, geometric, hipergeometric, negative binomial.
Expected value.

5. Continuous random varaibles. Uniform, exponential, gamma, gaussian.
Expected value.

6. Independent variables and joint laws.
Sum of two or more independent random variables. Poisson process. Maxima and minima of independent random variables.

7. Limit theorems. Markov and Chebyshev inequalities.Weak law of large numbers. Generating functions and a sketch of proof of the central limit theorem.


Core Documentation

Sheldon M. Ross, Calcolo delle Probabilita'. Apogeo, (2007).



F. Caravenna, P. Dai Pra, Probabilita'. Springer, (2013).

Reference Bibliography

Sheldon M. Ross, Calcolo delle Probabilita'. Apogeo, (2007). F. Caravenna, P. Dai Pra, Probabilita'. Springer, (2013).

Type of delivery of the course

Lecture, exercise sessions, written solutions available online.

Type of evaluation

2 intermediate written examinations (2 hours each) and 1 written final examination (3 hours).

teacher profile | teaching materials

Programme

Refer to the web-page of the course

Core Documentation

Sheldon M. Ross, Calcolo delle probabilita' (Apogeo Ed.)
F. Caravenna e P. Dai Pra, Probabilita' (Springer Ed.)

Reference Bibliography

Sheldon M. Ross, Calcolo delle probabilita' (Apogeo Ed.) F. Caravenna e P. Dai Pra, Probabilita' (Springer Ed.)

Type of delivery of the course

Exercises are solved on the blackboard - the proposed exercises aim at clarifying and practicing with the concepts seen during the lectures

Type of evaluation

Refer to the web-page of the course