| Study programme competencies |
| Code | Study programme competences |
| A1 | Capacidade para a resolución dos problemas matemáticos que poidan formularse na enxeñaría. Aptitude para aplicar os coñecementos sobre: álxebra lineal; xeometría; xeometría diferencial; cálculo diferencial e integral; ecuacións diferenciais e en derivadas parciais; métodos numéricos; algorítmica numérica; estatística e optimización. |
| B2 | Que os estudantes saiban aplicar os seus coñecementos ao seu traballo ou vocación dunha forma profesional e posúan as competencias que adoitan demostrarse por medio da elaboración e defensa de argumentos e a resolución de problemas dentro da súa área de estudo |
| B3 | Que os estudantes teñan a capacidade de reunir e interpretar datos relevantes (normalmente dentro da súa área de estudo) para emitiren xuízos que inclúan unha reflexión sobre temas relevantes de índole social, científica ou ética |
| B4 | Que os estudantes poidan transmitir información, ideas, problemas e solucións a un público tanto especializado como leigo |
| B5 | Que os estudantes desenvolvan aquelas habilidades de aprendizaxe necesarias para emprenderen estudos posteriores cun alto grao de autonomía |
| B6 | Ser capaz de concibir, deseñar ou poñer en práctica e adoptar un proceso substancial de investigación con rigor científico para resolver calquera problema formulado, así como de comunicar as súas conclusións –e os coñecementos e razóns últimas que as sustentan– a un público tanto especializados como leigo dun xeito claro e sen ambigüidades |
| B7 | Ser capaz de realizar unha análise crítica, avaliación e síntese de ideas novas e complexas |
| C1 | Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida. |
| C4 | Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse. |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| Participación en proxectos multidisciplinares de enxeñaría industrial. | A1 |
B3 B4 B5 |
C1 |
| Modelar estatiscamente sistemas e procesos complexos de todos os ámbitos da Enxeñaría Industrial. | A1 |
B3 B5 B6 B7 |
C1 |
| Resolver problemas con datos aplicando diversas técnicas estatísticas de forma efectiva para a enxeñería industrial. | A1 |
B2 B3 |
C4 |
| Contents |
| Topic | Sub-topic |
| Description of a statistical variable. | General Concepts. Frequency distributions. Graphical representations. Typical measures. |
| Description of several statistical variables. | Statistical vector. Linear regression. correlation. |
| Probability. | General Concepts. Axiomatic definition of Kolmogorov. Assigning probabilities: Laplace rule. |
| Conditional probability. | Definition of conditional probability. Independence of events. Theorems product, the total probability and Bayes. |
| One-dimensional random variables. | Concept of one-dimensional random variable. Discrete random variables and continuous. Transformation of random variables. Typical measures of a random variable. Inequality of Tchebychev. |
| Significant distributions Discreet. | Notable discrete random variables: discrete uniform distribution. Distribution Bernoulli. Binomial distribution. Geometric Distribution. Negative binomial distribution. Poisson distribution. hypergeometric distribution |
| Significant distributions continuous. | Continuous random variable notable: normal. The central limit theorem. Approach Distributions. Chi-square distribution of Pearson. Student's t-distribution. Distribution F Fisher-Snedecor. |
| Introduction to Statistical Inference. | General Concepts. Sampling. Generation of random variables. Concept of precise estimator. The sampling distribution of a statistic in precise. |
| Point estimation. | Properties of estimates. Methods of obtaining estimates. Precise estimate of the average. Precise estimator of the variance. Precise estimate of proportion. |
| Estimation of confidence intervals. | Concept of confidence interval. Confidence intervals for the mean. Confidence interval for the variance. Confidence interval for a proportion. Confidence intervals for the difference in averages. Confidence interval for the ratio of variances. Confidence interval for the difference in proportions. |
| Hypothesis tests | General Concepts. The critical significance level and a contrast. Power of a contrast. General procedure of hypothesis testing. Resistances for the medium. Contrast to the variance. Contrast to a ratio. Contrasts for the difference in averages. Contrast to the ratio of variances. Contrast to the difference in proportions. Contrasts position. Goodness-of-fit. Test of independence. Homogeneity tests. |
| Introduction to statistical quality control | Basic concepts. Six Sigma Methodology. Main statistical quality control tools |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A1 B2 B3 B4 C4 | 30 | 45 | 75 |
| Problem solving | A1 B2 B6 B7 C4 | 20 | 30 | 50 |
| ICT practicals | C1 | 10 | 10 | 20 |
| Objective test | A1 B3 B5 | 2.125 | 2.125 | 4.25 |
| Personalized attention | 0.75 | 0 | 0.75 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Guest lecture / keynote speech | The main contents of the subject will be explained with the help of suitable audiovisual means (laptop and video canon). |
| Problem solving | Problem-solving seminars will be held in intermediate-sized groups in order to establish the concepts presented in the master sessions and to provide knowledge of the methodologies for the practical resolution of statistical problems. |
| ICT practicals | Part of the practical classes will be carried out in a computer lab where, with the help of a statistical package (free software R), different practices will be developed using real or simulated data, previously provided to the students. |
| Objective test | At the end of the couse, a test type exam composed of 15-20 questions (practical and theoretical concerning with the subject contents) will be done. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| ICT practicals | C1 | Presentation of the works suggested by teachers with free statistical software R. | 25 |
| Objective test | A1 B3 B5 | Exame escrito tipo test constituido por entre 15 e 20 preguntas, tanto prácticas como teóricas, acerca da materia do curso. | 75 |
| Assessment comments | |||
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<b>Evaluation at the first opportunity</b><p>The
mark of the objective test will be weighted with the score corresponding to the optional delivery of works related to the practices carried out with statistical software R (maximum 1.5 points) and with the mark corresponding to the attendance at class (1 point), being necessary to obtain at least a score of 3.5 out of 10 in the objective test to be able to make this compensation.</p><p><strong>Evaluation at thesecond opportunity</strong></p><p>The evaluation will be done following the same procedure as at the first opportunity.</p><p>In the case of students with recognition of part-time dedication and academic exemption from attendance that decide not to attend classes, will be evaluated in the two opportunities as the rest of the students who are in a similar situation.</p> |
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| Sources of information |
| Basic |
http://www.r-project.org/ (). .
Montgomery D., Runger G. C. (2014). Applied Statistics and Probability for Engineers. Wiley
Cao R., Franciso M, Naya S., Presedo M., Vázquez M., Vilar J.A. y Vilar J.M. (2005). Introducción a la Estadística y sus aplicaciones. Editorial Pirámide |
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| Complementary | |
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| Recommendations | ||
| Subjects that it is recommended to have taken before | ||
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| Subjects that are recommended to be taken simultaneously |
| Subjects that continue the syllabus |
| Other comments | |
| <p>Para axudar a conseguir unha contorna inmediata sostida e cumprir co obxectivo da acción número 5: “Docencia e investigación saudable e sustentable&nbsp; ambiental e social” do "Plan de Acción Green Campus Ferrol:&nbsp;</p><p> A entrega dos traballos documentais que se realicen nesta materia:&nbsp;</p><p> • Solicitaranse en formato virtual e/ou soporte informático.&nbsp;</p><p> • Realizarase a través de Moodle, en formato dixital sen necesidade&nbsp; de imprimilos.&nbsp;</p><p> • En caso de ser necesario realizalos en papel:&nbsp;</p><p> - Non se empregarán plásticos.&nbsp;</p><p> - Realizaranse impresións a dobre cara.&nbsp;</p><p> - Empregarase papel reciclado.&nbsp;</p><p> - Evitarase a impresión de borradores.&nbsp;</p><p> • Débese de facer un uso sustentable&nbsp; dos recursos e a prevención de impactos negativos sobre o medio natural.&nbsp; &nbsp;</p><p> • Traballarase para identificar e modificar prexuízos e actitudes sexistas, e influirase&nbsp; na contorna para modificalos e fomentar valores de respecto e igualdade.&nbsp;</p><p> • Deberanse detectar situacións de discriminación e propoñeranse accións e medidas para corrixilas.</p> |