Probability and statistics
Summary
The course gives an introduction to probability and statistics for physicists.
Content
Probability: Basic concepts, conditional probability.
Random variables: Definitions density and distribution functions, expectation, variance, covariance, correlation, transformations, sums, generating functions, characteristic functions, conditional laws.
Discrete and continuous laws: Bernoulli, binomial, hypergeometric, Poisson, geometric, normal, exponential, Gamma, Cauchy, Weibull, Gumbel, chi-square.
Limit theorems: law of large numbers, central limit theorem
Introduction to statistics: frequentist, Bayesian viewpoints
Estimation: point estimation, bias, mean square error, maximum likelihood estimator
Hypothesis testing: errors, power, significance, chi^2
Keywords
probability and statistics
Learning Prerequisites
Important concepts to start the course
Calculus and basic linear algebra.
Learning Outcomes
By the end of the course, the student must be able to:
- Formulate
Assessment methods
Exam and midterm assessed coursework
Supervision
| Office hours | No |
| Assistants | Yes |
| Forum | Yes |
In the programs
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Probability and statistics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
Reference week
| Mo | Tu | We | Th | Fr | |
| 8-9 | |||||
| 9-10 | |||||
| 10-11 | |||||
| 11-12 | |||||
| 12-13 | |||||
| 13-14 | |||||
| 14-15 | |||||
| 15-16 | |||||
| 16-17 | |||||
| 17-18 | |||||
| 18-19 | |||||
| 19-20 | |||||
| 20-21 | |||||
| 21-22 |
Légendes:
Lecture
Exercise, TP
Project, other