This subject belongs to the M01 module Basic Education. The course is located at the begining of the the second year once the student has acquired basic knowledege in mathematics.

The thread that follows the subject is obtaining rational conclusions of empirical research

using statistical models.

Following this approach the basic principles are presented in the theory of

Probability: random variables, distribution of probability, statistical inference, sampling theory, parameter estimation and hypothesis testing.

The student will discover that statistics lends to professionals of various kinds in general and to engineers in particular, instruments that somehow mitigate the influence of chance and uncertainty.

Within the scope of this course students should know that the development of statistical methods has been a decisive factor in technological advancement. Even the problems presented by technological advances have prompted researchers to develop statistical procedures to be applied to the solution in multiple disciplines.

The statistical methods applied to sampling, experimental design and data processing in general,

ensure that the maximum information is obtained and the conclusions drawn are correct.

This course develops the following competencies and learning outcomes:

1. Students have the ability to gather and interpret relevant data (usually within their area

study) to inform judgments that include reflection on relevant social, scientific or ethical.



2. Ability to solve mathematical problems that may arise in engineering. ability to

apply knowledge of linear algebra; geometry; differential geometry; differential and calculation

integral; differential equations and partial differential; numerical methods; numerical algorithms; statistics and optimization.



3. Ability to solve problems with initiative, decision making, creativity, critical thinking and to communicate and transmit knowledge and skills in the field of Engineering in Industrial Organization



Learning outcomes:

• The clear and orderly exposition of fundamental concepts of physics, chemistry, calculus, algebra and statistics, high-level computer languages, the properties of representation systems and their normalization, and economic and the company.



• The reasoned resolution of problems that are completely specified, appropriately using multiple representations of the same phenomenon, justifying all steps with rigor, clarity and coherence and correctly interpreting the results obtained.



• The competent use of computer tools in software development, in solving mathematical problems with the help of symbolic computer packages and in computer-aided industrial design.



• The preparation and oral or written presentation of works in which the knowledge acquired in the module is applied to practical cases and general problems within the field of industrial engineering.

1 Introduction to probability

2 Random variables and their characteristics

3 Probability distribution models

4 Introduction to statistical inference, samples

5 Estimation

6 Hypothesis testing

The subject consists of 6 ECTS credits representing 150 hours. The tasks to be performed by the students are as follows:



1- Attendance: 60 hours:

In this course various teaching methodologies are used. Given the applied nature of the subject, the most used is problem solving. The master mode is also used to expose briefly by the teacher the basic theoretical contents necessary to address the practical cases with the right tools and to interpret the results correctly.

The resolution of issues and problems in the classroom will be made in a participatory manner. Problems and exercises will be provided to work individually or in groups, they will deepen the theoretical knowledge of the subject and relate statistic with other related areas. Questions, open discussions and teamwork are encouraged so that students acquire oral communication skills and the ability to synthesize.

The seminar is to deepen the selected descriptive statistics and simulation option.

In practical computer Excel will be used.

2- No attendance: 90 hours

• Final Assessment System
• Tools and qualification percentages:
  • Written test to be taken (%): 70
  • Team projects (problem solving, project design)) (%): 30

For calculations, the calculator must be used exclusively, the use of mobile phones or any other electronic device such as tablets, etc. is not permitted.



The continuous evaluation system will be used.



a) Teamwork (two people) deliverable and mandatory: 15% each. The maximum grade that can be obtained during the training period is 3 points that will be added to the final grade.



b) Written test to be taken on the official date established for the exam call. To pass the subject, students must obtain a minimum grade of 5 points (out of 10) in this written test. 70% of the grade obtained in this written test will be added to the final grade. Since this written test has a weight above 40%, failure to take this test means that the final grade will appear as NOT PRESENTED



In any case, students will have the right to be evaluated through the final evaluation system, regardless of whether or not they have participated in the continuous evaluation system. To do this, students must submit in writing to the teaching staff responsible for the subject the waiver of continuous evaluation, for which they will have a period of 9 weeks counting from the beginning of the semester, in accordance with the center's academic calendar.



The final evaluation system will consist of a final written exam that will contain 3 parts: theoretical content, practical exercises and knowledge of the seminars.

For calculations, the calculator must be used exclusively, the use of mobile phones or any other electronic device such as tablets, etc. is not permitted.



The final evaluation test of the extraordinary call will contain 3 parts: theoretical content, practical exercises and knowledge of the seminars. In the case of having obtained positive results during the continuous evaluation, these will be kept and the students will only be examined on the theoretical content and practical exercises of the final evaluation test.

“ESTADISTICA” Grafulla C. ETS de Ingenieros de Bilbao.

Basic bibliography

Título: Probabilidad y Estadística para Ingeniería y ciencias

Autores: Walpole, R.E. y otros

Editorial: Prentice Hall Año de Publicación: 2007



Título: Estadística, modelos y métodos. Vol. I.

Autores: Peña, Daniel.

Editorial: Alianza Universidad Año de Publicación: 1991



Título: Problemas de estadística

Autores: Martín Pliego, F.J y otros.

Editorial: Paraninfo Año de Publicación: 2011

In-depth bibliography

Título: Probabilidad y Estadística
Autores: DeGroot, M.H.
Editorial: Addison Wesley Iberoamericana Año de Publicación: 1987

Título: Probabilidad y Estadística para Ingeniería y ciencias
Autores: Devore, J.L.
Editorial: Thomson México Año de Publicación: 2005

Título: Estadística
Autores: Triola, M.F.
Editorial: Pearson. Addison Wesley Año de Publicación: 2009

Journals

Estadística Española. INE.
Publicaciones del Instituto Vasco de Estadística /Euskal Estatistika-Erakundea.
Annals of Statistics. Institute of Mathematical Statistics (IMS)
ESAIM: Probability and Statistics.
Société de Mathematiques Appliqués & Industrielles.

Web addresses

www.seeingstatistics.com
www.estadistico.com
www.eustat.es