Automotive Statistics and Measurements

Objectives

• Work with large amounts of data that may arise in daily life and extract the essence from it. (B1, B3, E1)
• Interpret this data and make decisions based on its analysis. (E1, T1)
• Use the appropriate tools to deal with statistical or probabilistic problems. (G1, T4)

Learning outcomes

• Analyze and solve probability, statistics and optimization problems.
• Identify and correctly use mathematical terminology, notation and methods.
• Discuss and critically analyze the results obtained in problem solving.
• Correctly uses specific software for analytical and numerical problem solving.
• Collects and interprets data and information on which to base their conclusions, which include, when necessary and pertinent, reflections on social, scientific or ethical issues within their field of study.

Competencies

General skills

• Combine scientific knowledge with technical skill and technological resources to solve the difficulties of professional practice.

Specific skills

• Understand the principles of mathematical theory in order to solve mathematical problems that may arise in engineering and apply knowledge to: linear algebra, geometry, differential geometry, differential and integral calculus, ordinary and partial differential equations, numerical methods, numerical algorithms, statistics and optimization.

Basic skills

• Students have demonstrated knowledge and understanding in a field of study that builds on general secondary education with the support of advanced textbooks and knowledge of the latest advances in this field of study.
• Students have the ability to gather and interpret relevant data (usually within their field of study) in order to make judgments that include reflection on relevant social, scientific and ethical issues.

Core skills

• Be a critical thinker before knowledge in all its dimensions. Show intellectual, cultural and scientific curiosity and a commitment to professional rigor and quality.
• Display professional skills in complex multidisciplinary contexts, working in networked teams, whether face-to-face or online, through use of information and communication technology.

Content

0. Introduction: statistics and probability in engineering
1. Probability
   1. Probability calculation
   2. Random variable
   3. Random variable models
2. Statistics
   1. Statistical inference
   2. Inference to compare populations
   3. Linear regression
3. Machine learning (machine learning, ML)
   1. Introduction, pretreatment and characteristics
   2. Classification models
   3. Operating measures

Evaluation

• Exams (65%)
  • Probability exam (30%), mid-course
  • Statistics exam (35%), at the end of the course
• Monitoring and completion of work during the course (15%)
  • Programming laboratory
  • Exercises
• ML group work (20%)

There is a retake exam in which the student can choose one of the two exams in the subject to retake: probability or statistics.

The part corresponding to monitoring during the course and ML group work cannot be recovered.

The grade to pass the subject must be 5 or higher. To pass it is not necessary to score a 5 or higher in each of the parts.

Methodology

In this subject, theoretical sessions are taught and exercises are designed and solved in the classroom. On the other hand, there is a set of individual guided practical sessions (programming laboratory), and a project. machine learning (ML) in groups. Regarding personal work, the student must follow the theoretical aspects of the subject, solve the proposed problems and make the final reports of the practical parts.

Bibliography

Key references

• González, José A. (2008). Estadística per a enginyers informàtics. Retrieved from http://hdl.handle.net.biblioremot.uvic.cat/2099.3/36774
• Pozo, F., Parés, N., Vidal, Y., i Mazaira, F. (2010). Probabilitat i estadística matemàtica: Teoria i problemes resolts. Retrieved from http://hdl.handle.net/2099.3/36649
• Prat Bartés, A. (1997). Métodos estadísticos: Control y mejora de la calidad. Retrieved from http://hdl.handle.net.biblioremot.uvic.cat/2099.3/36717
• Zaiats, V., Calle, M. L. (2001). Probabilitat i estadística: exercicis II. Universitat Autònoma de Barcelona.