Identifying Data 2020/21
Subject (*) Statistics Code 730G05012
Study programme
Grao en Enxeñaría Naval e Oceánica
Descriptors Cycle Period Year Type Credits
Graduate 1st four-month period
First Basic training 6
Teaching method Hybrid
Department Matemáticas
Naya Fernandez, Salvador
Naya Fernandez, Salvador
Tarrio Saavedra, Javier
General description Esta materia introduce os conceptos básicos da análise estatística de datos, desde a análise exploratoria (incluindo as principais ferramentas gráficas) ata a inferencia estatística, pasando pola introducción á probabilidade, o concepto de variable aleatoria e as ferramentas fundamentais do control estatístico da calidade, enfocando a súa docencia para a resolución de problemas prácticos en enxeñaría naval e oceánica.
Contingency plan 1. Modifications to the contents
The lessons are not modified.
2. Methodologies
*Teaching methodologies that are maintained
Teaching methodologies that are maintained
• Practices through ICT.
• Problem solving.
• Mixed test.
Teaching methodologies that are modified
Tools: Moodle, Microsoft Teams and email.
* Temporalization: Teams will be used as a tool to give the theoretical an practical lessons and the tutorials. Moodle will be used for the publication of content and notices, and for the evaluation of students (continuous evaluation and exam). E-mail will serve as a tool to resolve doubts and to exchange files and information in general.
3. Mechanisms for personalized attention to students

4. Modifications in the evaluation

All methodologies and their weighting in the global mark will be maintained: Problem solving (10%), consisting of the delivery of exercises; practices through ICT (60% of the global mark), defined by the presentation of works proposed by the teachers with the free statistical software R; and the mixed test (40%), consisting of a test-type examination consisting of between 15 and 20 questions, both practical and theoretical, about the subject of the course (it will be carried out in distance mode and also in the synchronous mode).

5. Modifications to the bibliography or webgraphy

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
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
B5 That the students developed those skills of learning necessary to start subsequent studies with a high degree of autonomy
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.
C4 Recognizing critically the knowledge, the technology and the available information to solve the problems that they must face.
C7 Capacidade de traballar nun ámbito multilingüe e multidisciplinar.

Learning aims
Learning outcomes Study programme competences
Adquirir coñecementos, aptitudes e habilidades para a análise estatística de datos que conleve a extracción de coñecemento útil na industria e en todos os ámbitos da enxeñaría naval e oceánica. A1
Modelar estatísticamente sistemas e procesos complexos de todos os ámbitos da Enxeñaría Naval e Oceánica. A1
Resolver problemas con datos aplicando diversas técnicas estatísticas de forma efectiva para a enxeñería naval. B2

Topic Sub-topic
The following topics develop the contents established in the tab of the Memoria de Verificación, which are: Statistical data analysis. Probability calculation. Point estimation and confidence intervals. Hypothesis testing. Introduction to statistical quality control.
Description of a statistical variable. General Concepts.
Frequency distributions.
Plots and data visualization.
Measurements of position, variability and shape.
Description of several statistical variables. Statistical vector.
Linear regression.
Probability. General Concepts.
Axiomatic definition of Kolmogorov.
Assigning probabilities: Laplace rule.
Conditional probability. Definition of conditional probability.
Independence of events.
Theorems of product, Bayes and law of total probability.
One-dimensional random variables. Concept of one-dimensional random variable.
Discrete and continuous random variables.
Transformation of random variables.
Typical measures of a random variable. Inequality of Tchebychev.
Probability distributions for discrete variables Discrete random variables: discrete uniform distribution.Bernoulli distribution. Binomial distribution. Geometric distribution. Negative binomial distribution. Poisson distribution. hypergeometric distribution
Probability distributions for continuous variables Probability distributions of continuous random variables: Normal distribution. The central limit theorem.Approximate (limit) relationships between probability distributions. Pearson's Chi-square distribution. Student's t-distribution. Fisher-Snedecor's F distribution. Other distributions.
Introduction to Statistical Inference. General concepts. Sampling. Generation of random variables. Point estimation concept. The sampling distribution of a point estimator.
Point estimation. Properties of the estimators. Methods of obtaining estimators. Point estimator of the mean. Point estimator of variance. Point estimator of a proportion.
Estimation of confidence intervals. Confidence interval concept. Confidence intervals for the mean. Confidence interval for variance. Confidence interval for a proportion. Confidence intervals for the difference of two means. Confidence interval for the quotient of two variances. Confidence interval for the difference of two proportions.
Hypothesis tests General concepts. Critical level (p-value) and significance level of a hypothesis test. Power of a test. General procedure for hypothesis testing. Tests for the mean. Test for variance. Test for a proportion. Tests for the difference of two means. Test for the ratio of two variances. Test for the difference of two proportions. Position Tests. Goodness of fit tests. Independence tests. Homogeneity tests.
Introduction to statistical quality control Basic concepts. Six Sigma Methodology. Main statistical quality control tools.

Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Guest lecture / keynote speech A1 B2 B3 B5 C1 30 30 60
Problem solving B5 B6 C1 20 20 40
ICT practicals C1 C4 C7 10 35 45
Mixed objective/subjective test A1 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 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.
Mixed objective/subjective 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
Guest lecture / keynote speech
There will be lectures where the teacher will explain, with the help of appropriate audiovisual media, the main contents of the course. Debate will be encouraged among students and between students and teacher.

In the case of students with academic dispensation, person-to-person and virtual tutorials (e-mail, videoconferences) will be available, which will allow the student to follow properly the subject.

All teaching methodologies are maintained, changing only the mechanisms of personalized attention to students, which will consist of virtual classes and virtual tutorials.

Methodologies Competencies Description Qualification
Problem solving B5 B6 C1 Delivery of exercices. 10
ICT practicals C1 C4 C7 Presentation of the works suggested by teachers with free statistical software R. 30
Mixed objective/subjective test A1 Exame escrito tipo test constituido por entre 15 e 20 preguntas, tanto prácticas como teóricas, acerca da materia do curso. 60
Assessment comments
Evaluation at the first opportunity

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 3 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.

Evaluation at thesecond opportunity

The evaluation will be done following the same procedure as at the first opportunity.

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.

Sources of information
Basic (). .
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


Subjects that it is recommended to have taken before

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments

To help to achieve a sustainable environment and meet the objective of action number 5: “Healthy and sustainable environmental and social teaching and research” of the "Green Campus Ferrol Action Plan:

1.- The delivery of the documentary works carried out in this subject:

1.1. It will be requested in virtual format and/or computer support.

1.2. It will be done through Moodle, in digital format without the need to print them

1.3. If done on paper:

-Plastics will not be used.

- Double-sided prints will be made.

- Recycled paper will be used.

- Draft printing will be avoided.

2.- A sustainable use of resources and the prevention of negative impacts on the natural environment must be made.

3.- The importance of ethical principles related to the values ??of sustainability in personal and professional behavior must be taken into account.

4.- As it is included in the different regulations of application for university teaching, the gender perspective must be incorporated in this subject (non-sexist language will be used, bibliography of authors of both sexes will be used, intervention in student class will be encouraged and students ...).

5.- We will work to identify and modify prejudices and sexist attitudes, and the environment will be influenced to modify them and promote values ??of respect and equality.

6. Situations of discrimination based on gender must be detected and actions and measures will be proposed to correct them.

7. The full integration of students who, due to physical, sensorial, psychic or sociocultural reasons, experience difficulties in an ideal, egalitarian and profitable access to university life will be facilitated

(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.