Probability and statistics 1 - 3MMPS1

Goal(s)

Fundamentals of statistics and probability

Responsible(s)

Olivier FRANCOIS, Christophe DUTANG

Content(s)

The course is a full tutorials in class room for 12 weeks.

The language to be learned is R.

Core concepts include

• Vectors, matrices, data frames in R
• Visualization and summary of data (data.frame, summary, plot, quantile, table, hist)
• Random variable, probability distribution, density, expectation, variance
• Sum of random variables, stability of Gaussian and gamma distributions
• Convergence of the empirical average, law of large numbers, central limit theorem, Monte-Carlo methods
• Sampling, parametric inference, statistical error
• Hypothesis tests, confidence intervals, interpretation of p-values
• Couple of random variables, joint, conditional and marginal distributions, dependency, conditional expectation
• Linear model, correlation
• Regression for 1 or 2 variables, confusion factor, mediation factor
• Predicitive approach, Bayes rules

Elementary calculus in discrete probability, linear algebra

Test

Evaluation : 33% of Devoir à la maison and 67% of Examen sur machine (3h00)

Resit : 33% of Devoir à la maison (reported score) and 67% of Examen sur machine (2h00)

First Session:
The grade for the course unit (N1) is a weighted average of the continuous assessment (CC) and the final exam (ET1).

The continuous assessment (CC) will take into account participation in tutorials and the submission of assignments.
The final exam (ET1) will be an individual 3-hour exam held in a computer lab.

Second Session:
The evaluation will be based on a 1-hour exam (ET2).

Authorized documents: A handwritten A4-format summary
Prohibited documents: Any other document or material

Calendar

The course exists in the following branches:

• Curriculum - Core curriculum - Semester 5

Additional Information

Course ID : 3MMPS1
Course language(s):

You can find this course among all other courses.