Identifying Data  2020/21  
Subject (*)  Statistics  Code  730G05012  
Study programme 


Descriptors  Cycle  Period  Year  Type  Credits  
Graduate  1st fourmonth period 
First  Basic training  6  
Language 


Teaching method  Hybrid  
Prerequisites  
Department  Matemáticas 

Coordinador 



Lecturers 



Web  
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). Email 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 testtype 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 

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 
B2 B3 B5 

Modelar estatísticamente 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.  B2 
C1 C4 C7 
Contents 
Topic  Subtopic 
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. Correlation. 
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. 
Onedimensional random variables.  Concept of onedimensional 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 Chisquare distribution. Student's tdistribution. FisherSnedecor'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 (pvalue) 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. 
Planning 
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 
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  Problemsolving seminars will be held in intermediatesized 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 1520 questions (practical and theoretical concerning with the subject contents) will be done. 
Personalized attention 


Assessment 
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
The Evaluation at thesecond opportunity The evaluation will be done following the same procedure as at the first opportunity. In 
Sources of information 
Basic 
http://www.rproject.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 LimusaWiley 


Complementary  

Recommendations 
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.  Doublesided 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 (nonsexist 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 