Linear algebra Calculus Programming

By the end of this course, students will be able to have: 1. Knowledge and understanding of the statistic principles underlying their branch of engineering 2. The ability to apply their knowledge and understanding to identify, formulate and solve statistic problems using established methods 3. The ability to apply their knowledge and understanding to analyse engineering products, processes and methods 4. An understanding of statistics methodologies, and an ability to use them 5. The ability to select and use appropriate statistic tools and methods 6. The ability to combine theory and practice to solve engineering problems 7. An understanding of applicable statistic techniques and methods, and of their limitations

RA1.1 Knowledge and understanding of the scientific and mathematical principles underlying their branch of engineering. RA2.1 The ability to apply their knowledge and understanding to identify, formulate and solve engineering problems using established methods. RA2.2 The ability to apply their knowledge and understanding to analyse engineering products, processes and methods. RA3.2 An understanding of design methodologies, and an ability to use them. RA5.1 The ability to select and use appropriate equipment, tools and methods. RA5.2 The ability to combine theory and practice to solve engineering problems. RA5.3 An understanding of applicable techniques and methods, and of their limitations. CB1 Students have demonstrated possession and understanding of knowledge in an area of study that builds on the foundation of general secondary education, and is usually at a level that, while relying on advanced textbooks, also includes some aspects that involve knowledge from the cutting edge of their field of study. CB2 Students are able to apply their knowledge to their work or vocation in a professional manner and possess the competences usually demonstrated through the development and defence of arguments and problem solving within their field of study. CG1 Ability to resolve problems with initiative, creativity decision-making and critical reasoning skills, and to communicate and transmit knowledge, skills and abilities in the Industrial Engineering area. CG8 knowledge and capacity to apply quality principles and methods. CG11 Capacity to solve mathematic problems arising in engineering. Aptitude for applying knowledge of: linear algebra; geometry; differential geometry; differential and integral calculus; differential equations and partial derivatives: numerical methods; numerical algorithms; statistics and optimization.

1. Descriptive statistics 1.1. Qualitative data vs quantitative data 1.2. Descriptive statistics for one variable 1.3. Descriptive statistics for two variables 2. Probability 2.1. Introduction to probability 2.2. Events and operations with events 2.3. Definition and properties of probability 2.4. Conditional probability and independence 2.5. The law of total probability 2.6. Bayes' theorem 3. Random variables 3.1. Concept of random variable 3.2. Discrete random variables 3.3. Continuous random variables 3.4. Characteristic measures of a random Variable 3.5. Independence of random variables 4. Distribution models 4.1. Binomial 4.2. Geometric 4.3. Poisson 4.4. Uniform (continuous) 4.5. Exponential 4.6. Normal (CLT) 5. Statistical inference 5.1. Introduction 5.2. Estimators and their sampling distributions 5.3. Confidence intervals 5.4. Hypothesis testing 6. Quality control 6.1. Introduction to quality control 6.2. Control charts for variables 6.3. Control charts for attributes 7. Linear regression 7.1. Introduction 7.2. Simple linear regression 7.3. Multiple linear regression

- Lectures: 2,2 ECTS - Problem solving sessions: 1,8 ECTS - Computes sessions: 1 ECTS - Evaluation sessions (continuous evaluation and final exam): 1 ECTS