Objectives of Programme's Learning Outcomes

• Understand the theoretical and methodological fundamentals in science and engineering to solve problems involving these disciplines
• Identify, describe and explain basic scientific and mathematical principles
• Identify, describe and explain the basic principles of engineering particularly in their specialising field
• Select and rigorously apply knowledge, tools and methods in sciences and engineering to solve problems involving these disciplines

Learning Outcomes of UE

- Understand and explain the basic concepts of probability and some important results (law of large numbers, Central Limit Theorem);- Solve simple applications implementing these concepts and results in a number of concrete situations (gambling, election polls, queues, fault diagnosis, ...); - Construct an interval containing almost certainly the value of a parameter of the distribution of a variable al- Testing the assumptions made on the value of parameters associated with random variables, and other assumptions such as independence, fit and homogénéit- Establish a linear regression model to an explanatory variable.

UE Content: description and pedagogical relevance

notions of probability: random variables and distribution; classical distributions; vectors al independence, correlation, normal distribution; laws of large numbers; central limit theorem, characteristic function, approximation to the binomial distribution by the normal distribution and the Poisson distribution; modeling real situations by probability (eg, queues, Google PageRank).

Notions of statistics: basic descriptive statistics in one and two dimensions (sample frequency, graphics); correlation; regression; independence; estimate average intervals, variance, proportion; regression coefficient; maximum likelihood method; hypothesis testing (population mean, proportion, variance, comparison of means and variances, fit, independence); linear regression model (in one variable).

Prior Experience

Calculus.