Objectives of Programme's Learning Outcomes

• Implement an engineering approach dealing with a set problem taking into account technical, economic and environmental constraints
• Understand the stages of an engineering approach
• Design, evaluate and optimise solutions addressing the problem
• Identify and acquire the information and skills needed to solve the problem
• 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
• Communicate in a structured way - both orally and in writing, in French and English - giving clear, accurate, reasoned information
• Argue to and persuade customers, teachers and a board both orally and in writing
• Demonstrate thoroughness and independence throughout their studies
• Identify the different fields and participants in engineering
• Demonstrate self-awareness, asses themself, and develop appropriate learning strategies.
• Direct their choice of modules within their degree programme in order to develop a career plan in line with the realities in the field and their profile (aspirations, strengths, weaknesses, etc.)
• Develop their scientific curiosity and open-mindedness
• Learn to use various resources made available to inform and train independently

Learning Outcomes of UE

Analyse data to extract statistical information. Discuss statistical quantities describing data. Represent data graphically. Study the linear dependancy of two random quantities. Manipulate probabilities and use their properties to infer conclusions. Use Bayes formula to infer new probabilities. Define the notion of random variables. Compute the moments of a random variable and of a vector of random variables. Manipulate the associated properties. Manipulate the specific random variables studied in the course. Understand and manipulate the fundamental theorems of the theory of probabilities. Solve problems of inference and estimation. Compute confidence intervals. Implement the various statistical tests described in the course. Explain the underlying ideas behind those tests.

UE Content: description and pedagogical relevance

One-dimensional and multi-dimensional descriptive statistics. Probability theory. Element of combinatorial calculus. Random variables: definition and properties. Specific random variables. Bienayme-Tchebycheff inequality. Bernoulli's theorem. De Moivre's theorem. Central-Limit Theorem. Asymptotic results. Statistical inference: confidence intervals, estimates, statistical tests.

Prior Experience

Mathematics I.