| Study programme competencies |
| Code | Study programme competences |
| A1 | Skill for the resolution of the mathematical problems that can be formulated in the engineering. Aptitude for applying the knowledge on: linear algebra; geometry; differential geometry; differential and integral calculation; differential equations and in partial derivatives; numerical methods; algorithmic numerical; statistics and optimization |
| B1 | That the students proved to have and to understand knowledge in an area of study what part of the base of the secondary education, and itself tends to find to a level that, although it leans in advanced text books, it includes also some aspects that knowledge implicates proceeding from the vanguard of its field of study |
| B2 | That the students know how to apply its knowledge to its work or vocation in a professional way and possess the competences that tend to prove itself by the elaboration and defense of arguments and the resolution of problems in its area of study |
| B3 | That the students have the ability to bring together and to interpret relevant data (normally in its area of study) to emit judgments that include a reflection on relevant subjects of social, scientific or ethical kind |
| B6 | Be able to carrying out a critical analysis, evaluation and synthesis of new and complex ideas. |
| C1 | Using the basic tools of the technologies of the information and the communications (TIC) necessary for the exercise of its profession and for the learning throughout its life. |
| C2 | Coming across for the exercise of a, cultivated open citizenship, awkward, democratic and supportive criticism, capable of analyzing the reality, diagnosing problems, formulating and implanting solutions based on the knowledge and orientated to the common good. |
| C5 | Assuming the importance of the learning as professional and as citizen throughout the life. |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| Participación en proxectos multidisciplinares de enxeñaría naval e oceánica. | A1 |
B1 B2 B3 |
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| Modelar estatiscamente sistemas e procesos complexos de todos os ámbitos da Enxeñaría Naval e Oceánica. | A1 |
B6 |
C1 |
| Resolver problemas con datos aplicando diversas técnicas estatísticas de forma efectiva para a enxeñería naval. | B1 B2 |
C1 C2 C5 |
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| 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. |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A1 B2 B3 C1 | 21 | 36.75 | 57.75 |
| Problem solving | B1 B6 C1 C2 | 21 | 36.75 | 57.75 |
| ICT practicals | C1 | 9 | 13.5 | 22.5 |
| Multiple-choice questions | A1 B1 B2 C5 | 1.25 | 2.5 | 3.75 |
| Objective test | A1 B1 | 2.5 | 5 | 7.5 |
| 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 | Part of the practical classes will be held in a computer lab, where with the help of statistical package (free software R) will be carried out with different practices simulated or actual data that have been previously provided to students. |
| Problem solving | If you compose a presentation of the subject, where in addition to describing the main data Mismo, establishing a discussion of solving problems. |
| ICT practicals | Be conducted lectures where the teacher will explain, with the help of appropriate audiovisual media (laptop and video projector), oos main contents of the course. |
| Multiple-choice questions | Multiple-choice test questions 10-20 of the program. |
| Objective test | There will be a test at the end of the course which consist in a series of practical exercises and reolución a test / exam multiple choice. |
| 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. | 30 |
| Objective test | A1 B1 | Written exam of 20 multiple choice questions of the course and the resolution of one or two problems. Be weighed with the note of the work (maximum 1.5 points) and the attendance (1 point), being necessary to get by at least a 3.5 this review (on one note 10) to make this compensation. | 50 |
| Multiple-choice questions | A1 B1 B2 C5 | Continuous assessment of of the program with questions and exercises. | 20 |
| Assessment comments | |||
| Sources of information |
| Basic |
http://www.r-project.org/ (). .
Cao R., Franciso M, Naya S., Presedo M., Vázquez M., Vilar J.A. y Vilar J.M. (2001). Introducción a la Estadística y sus aplicaciones. Editorial Pirámide
Montgomery, D. C. & Runger, G. C. (2004). Probabilidad y Estadística aplicadas a la Ingeniería.. Editorial Limusa-Wiley |
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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 | |