37529 - Mathematical Probability and Statistics 1

Learning outcomes

At the end of the course the student will know the basics of Probability theory and Statistics. He will be able to make simple models to describe problems under uncertainty conditions.

Course contents

Part 1. Probability spaces. Independence and conditional probability.

Part 2. Random variables and integration. Expectation and independence.

Part 3. Sequences of random variables. Law of large numbers. Characteristic function. Central limit theorem.

Part 4. Conditional distribution and expectation.

Part 5. Basics of statistics and inference.

Detailed programme available at

https://docs.google.com/document/d/1DffJ8fgrKfsaLvMX3a3TxL6BZzDWn3sjYl9hSmqOXR8/edit?usp=sharing

 

Readings/Bibliography

See 

https://docs.google.com/document/d/1DffJ8fgrKfsaLvMX3a3TxL6BZzDWn3sjYl9hSmqOXR8/edit?usp=sharing

Teaching methods

Classroom lectures

Assessment methods

At the end of the course each student will take a written and oral exam in which they will answer questions about the subjects covered in the program.

Teaching tools

Theoretical and computer exercises.

Links to further information

https://docs.google.com/document/d/1DffJ8fgrKfsaLvMX3a3TxL6BZzDWn3sjYl9hSmqOXR8/edit?usp=sharing

Office hours

See the website of Andrea Pascucci