Checking date: 24/04/2024

Course: 2024/2025

Bachelor in Robotics Engineering (Plan: 478 - Estudio: 381)

Coordinating teacher: MINGUEZ SOLANA, ROBERTO

Department assigned to the subject: Statistics Department

Type: Basic Core
ECTS Credits: 6.0 ECTS


Branch of knowledge: Social Sciences and Law

Requirements (Subjects that are assumed to be known)
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
Skills and learning outcomes
Description of contents: programme
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
Learning activities and methodology
- Lectures: 2,2 ECTS - Problem solving sessions: 1,8 ECTS - Computes sessions: 1 ECTS - Evaluation sessions (continuous evaluation and final exam): 1 ECTS
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50

Calendar of Continuous assessment

Extraordinary call: regulations
Basic Bibliography
  • MONTGOMERY, D.C., RUNGER, G.C. Applied Statistics and Probability for Engineers. John Wiley & Sons. 2003
  • NAVIDI, W. Statistics for Engineers and Scientists. McGraw-Hill. 2006
  • SONG, TT. Fundamentals of Probability and Statistics for Engineers. John Wiley & Sons. 2004
  • WASSERMAN, L. All of Statistics. Springer-Verlag. 2004
Additional Bibliography
  • GUTTMAN, L., WILKS, S.S., HUNTER, J.S. Introductory Engineering Statistics. Wiley. 1992

The course syllabus may change due academic events or other reasons.