Educational guide  
IDENTIFYING DATA  2020_21  
Subject  NUMERICAL AND ESTATISTICAL METHODS  Code  00707006  
Study programme 


Descriptors  Credit.  Type  Year  Period  
6  Basic Training  First  Second 

Language 


Prerequisites  
Department  MATEMATICAS 

Coordinador 

asaes@unileon.es mmlopc@unileon.es 

Lecturers 


Web  http://  
General description  First part is an introduction to Numerical Methods. We present the main techniques about interpolation and curve fitting, and numerical integration. We also study algorithms to obtain numerical solutions of systems of linear and nonlinear equations. Second part is devoted to Statistics. We focus our study on exploratory data analysis, Probability and Distribution Theory and Statistical Inference.  
Tribunales de Revisión 


Competencias 
Code  
B5655  
B5656  
B5664  
B5665  
B5666  
C1  
C4  
C5 
Learning aims 
Competences  
The students understand the main concepts of numerical and statistical methods, and they apply them in solving mathematical problems appearing in engineerings.  B5655 
C1 

Students show skills and abilities in analysis, synthesis, critical reasoning and decision making.  B5656 B5664 B5665 

Students apply the studied concepts in the elaboration of correct argumentations and reasonings. They are able to face up with situations where they need new mathematical knowledge and techniques. They have developed their autonomous learning skills.  C5 

Students are able to communicate mathematical ideas and information in oral and written form.  B5656 B5666 
C4 
Contents 
Topic  Subtopic 
PART I: NUMERICAL METHODS  1: NUMERICAL SOLUTION OF NONLINEAR EQUATIONS IN ONE VARIABLE. Iterative methods: bisection, fixed point and NewtonRaphson. Analysis of error. 2: POLYNOMIAL INTERPOLATION AND APPLICATIONS. Lagrange interpolation polynomial. Hermite interpolation. Cubic splines. 3: LEAST SQUARES DATA FITTING. Regression line. Linear models. Nonlinear models. 4: NUMERICAL INTEGRATION METHODS. Rules of rectangles, midpoint, trapezoids and Simpson 
PART II: STATISTICAL METHODS  1: DESCRIPTIVE STATISTICS. Data types and graphical representation. Scatter plots and correlation coefficient. 2: PROBABILITY. Basic calculation of probabilities: intersections, unions and conditional probability. Bayes' theorem. 3: RANDOM VARIABLES AND PROBABILITY DISTRIBUTITONS. Probability distribution of discrete and continuous random variables. Some models: uniform, binomial, Poisson, normal and other probability distributitons. 4: STATISTICAL INFERENCE. Confidence intervals and hypothesis testing. 
Planning 
Methodologies :: Tests  
Class hours  Hours outside the classroom  Total hours  
Problem solving, classroom exercises  20  20  40  
Practicals using information and communication technologies (ICTs) in computer rooms  12  12  24  
Assignments  0  12  12  
Lecture  22  22  44  
Mixed tests  6  24  30  
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. 
Methodologies 
Description  
Problem solving, classroom exercises  Students are taught how the should act and they act themselves in solving numerical and statistical problems appearing in Engineering. 
Practicals using information and communication technologies (ICTs) in computer rooms  
Assignments  They consist of various activities: responding questionnaires, uploading exercises, homework assignments, and/or team works. Many of these activities can be done electronically via moodle. 
Lecture  Students are given the instruction on theoretical concepts and practical methods needed to solve problems. 
Personalized attention 


Assessment 
Description  Qualification  
Assignments  To be evaluated: knowledge and comprehension of the subject, and correct interpretation of results. Works done in "unauthorized groups" will be graded 0 points. In the case of noncontact activities, the inperson explanation of the submitted works may be required, as well as proposing to make some modification. Works and assignments are not reevaluated in the second call.  20%  
Mixed tests  "Mixed" means that tests are written and may also require the use of computer programs. Two tests will be done, one for each part A and B, and each of them is worth 40% of total. Aspects to be evaluated: knowledge and comprehension of the subjetc, correct use of mathematical and statistical language, correct writing and interpretation of results, and ability in the use of computer software.  80%  
Other comments and second call  
In all tests: the use of mobile phones and other electronic devices is strictly forbidden, and will result in grade zero. Only the material specifically allowed by the instructors may be used. Second call. Students may choose between these two options:  maintain/preserve the grades obtained in all works and assignments (20%) and repeat one or both written tests. If either part A or B is not repeated in the second call, the grade corresponding to that part obtained in the first call will be maintained in the second call.  remove/withdraw all works and assigments from the calculation of the final grade, in this case each of the written tests will be worth 50%. 
ADDENDUM 
Contingency plan due to COVID19 emergency conditions that prevents from presence based teaching 
COVID19 Teaching Guide Addendum Access Link 
Sources of information 
Access to Recommended Bibliography in the Catalog ULE 
Basic 
ARRIAZA GÓMEZ, A.J. y otros, Estadística básica con R y RCommander, Universidad de Cádiz, 2006 BURDEN, R.L y FAIRES, J.D., Métodos Numéricos, Thomson, 2006 Chapra, S.C., Canale, R.P., Métodos Numéricos para Ingenieros, McGrawHill, 2007 MILTON, S., Probabilidad y estadística con aplicaciones para ingeniería y ciencias computacionales, McGrawHill, 2004 DEVORÉ, J.L. , Probabilidad y Estadística para Ingeniería y Ciencias, Thomson, 2005 WALPOLE R. & MYERS R. & MYERS S., Probabilidad y Estadística para ingenieros, PrenticeHall, 1999 CORDERO BARBERO, Alicia, y otros, Problemas resueltos de métodos numéricos, Thomson, 2006 ARRIAZA GÓMEZ, A.J. y otros, Sitio web del libro Estadística básica con R y RCommander, http://knuth.uca.es/ebrcmdr/, 2008 
Complementary  
Recommendations 
Subjects that it is recommended to have taken before  
