Double Degree in Electronic Systems Engineering in Communications and Management of ICTS La Salle Campus Barcelona

Double Degree in Electronic Systems Engineering in Communications and in Engineering in the Management of ICTs

La Salle Campus Barcelona offers 5 double degrees in the ICT Engineering field. With the double degrees, you can finish the university studies in 5 academic years with two official degree qualifications.

Statistics and Mathematical Analysis

Description: 

Stobaeus recounts, in his book Florilegium, an anecdote that took place with Euclid on the first day of class. The Greek mathematician had just finished explaining the first theorem when a student interrupted him, asking: “What benefit will I get from this?” Euclid called for a slave and ordered: “Give him a coin, since he needs to profit from what he learns.”


To learn to appreciate mathematics, as Abraham Flexner would say, we must abolish the word utility and thus free the human spirit. Learning and doing mathematics, first and foremost, is a personal experience. Mathematics connects two faculties: intuition and reason. It is an intimate, silent yet vibrant dialogue between immediacy and reflection. Every small step we take is guided by intuition, but it is not a firm step until reason validates it.

 

David Bessis, in his book Mathematica: Une aventure au cœur de nous-mêmes, presents an interesting example related to this idea. We draw a circle on a sheet of paper and ask ourselves: at most, how many points will a straight line crossing the page intersect the circle? Intuition gives us an immediate answer: a single straight line will intersect the circle at most at two points. This intuitive solution is as certain as it is simple to reach. However, if we want to prove it formally, we’ll need the equation of the line, the equation of the circle, and we’ll have to solve a system to find the points of intersection. The algebraic solution gives us three possibilities: the line intersects the circle at two points, at no point, or at a single point (a tangent line). Thus, the reasoned answer confirms our initial intuition: at most, the line intersects the circle at two points. To validate this, we’ve used mathematical language. Moreover, in every step (formulating the proof, setting up the system, solving it, etc.) no matter how small each step may be, we constantly rely on intuition.

These continuous validations lead to an improvement in our mathematical intuition, which we can clearly observe evolving over time. In this sense—and also in other, more mundane ways that we won’t delve into now—mathematics invites us, above all, to experience its practice as a journey of personal growth.

 

Everything discussed so far is independent of the specific mathematics syllabus you may be working on. It applies equally to the most basic exercises in primary school and to the more complex topics in Algebra or Calculus at university level. Every course is a new opportunity to discover and deepen this understanding. The course in Statistics and Mathematical Analysis is one such opportunity. The Mathematical Analysis part is an extension of differential calculus to functions of more than one variable. In the second semester, we will focus on Probability and Statistics, which will likely be new to everyone.


If you’ve made it this far and are still unsure of what benefit you might gain from all this, let me add that this course also lays the mathematical foundations for many subjects you’ll encounter later on, such as: Signals and Transmission Systems, Knowledge-Based Systems, Electromagnetic Propagation, Acoustic Engineering, Audio and Speech Processing, Digital Signal Processing, Data Mining, Physical Simulation, Communications in Hostile Environments, Data Network Interconnection, Robotics, Optical Communications, Digital Image Processing, and more.


However, as mentioned earlier, we invite you to free yourselves from the need to find a practical use for mathematics, so that you can instead focus on the discipline itself, which is, in truth, a way of focusing on yourselves.



Type Subject
Obligatoria no de Primer
Semester
Annual
Course
2
Credits
8.00

Titular Professors

Previous Knowledge: 

Differential and Integral one variable functions calculus. Vectors spaces and their basic properties.

Objectives: 

The aim of this course is to further develop students' knowledge of the mathematical tools required for an engineering degree.

Contents: 


Part 1. Functions of Several Variables

  1. Previous Definitions
  2. Functions of Several Real Variables
    2.1. Definition and Domain
    2.2. Limits
    2.3. Continuity
    2.4. Graphs, Level Curves and Surfaces
  3. Total and Partial Increment of a Function. Differential of a Function
  4. Partial Derivatives
    4.1. Definition
    4.2. Geometric Interpretation
    4.3. Generalization to Functions of More Than Two Variables
    4.4. Higher-Order Partial Derivatives
  5. Differentiability
    5.1. Errors and Differentials
  6. Directional Derivative
    6.1. Definition and Geometric Interpretation
    6.2. Differentiability and Directional Derivative
    6.3. Gradient: Definition and Properties
  7. Tangent Plane and Normal Line to a Function
  8. Differentiation of Implicit and Composite Functions
  9. Maxima and Minima
  10. Constrained Optimization. Lagrange Multipliers Method

Part 2. Multiple Integrals

  1. Double Integrals
    1.1. Domain and Properties
    1.2. Computation of Double Integrals
    1.3. Change of Variables. Jacobian. Polar Coordinates
  2. Triple Integrals
    2.1. Domain and Properties
    2.2. Computation of Triple Integrals
    2.3. Change of Variables. Cylindrical and Spherical Coordinates

Part 3. Probability and Statistics

  1. Combinatorics
    1.1. Variations
    1.2. Permutations
    1.3. Combinations
  2. Introduction to Probability
    2.1. Previous Definitions
    2.2. Operations on Events
    2.3. Definitions of Probability
    2.4. Conditional Probability
    2.5. Law of Total Probability
    2.6. Bayes' Theorem
    2.7. Independent Events
  3. Random Variables
    3.1. Previous Definitions
    3.2. Discrete Random Variables
    3.2.1. Distribution Function
    3.3. Continuous Random Variables
    3.3.1. Distribution Function
    3.3.2. Density Function
    3.4. Mathematical Expectation and Moments
    3.4.1. Expectation
    3.4.2. Variance and Standard Deviation
    3.5. Markov and Chebyshev Inequalities
  4. Univariate Distributions
    4.1. Discrete Distributions
    4.1.1. Binomial
    4.1.2. Poisson
    4.2. Continuous Distributions
    4.2.1. Uniform
    4.2.2. Normal
  5. Bivariate Distributions
    5.1. Discrete Distributions
    5.2. Continuous Distributions
    5.3. Distribution Functions (Cumulative)
    5.4. Marginal Distributions
    5.5. Independent Random Variables
    5.6. Conditional Distributions
    5.7. Covariance and Correlation
    5.8. Linear Regression Between Two Random Variables
  6. Sampling Theory
    6.1. Central Limit Theorem
    6.2. Sampling
    6.3. Hypothesis Testing

Methodology: 

The course is taught in 2 weekly lessons lasting 100 minutes each. The usual dynamics of each class will consist of a combination of theoretical explanations always followed by exercises that exemplify what has just been explained. Applied methodologies: master class, problems and exercises class. Additionally, the eStudy provides resources for the student to carry out self-learning activities (by viewing videos indexed according to their content) and self-assessment (by conducting non-evaluable questionnaires on the content).

Evaluation: 


The course is organized into two semesters. To pass the course, students must obtain a grade of 5 or higher in each semester (either in the regular or extraordinary examination period). In this case, the final course grade will be the arithmetic mean of the two semester grades. Otherwise, the course will be considered failed.

Evaluation Criteria: 


The following aspects will be assessed:

  • The correct application of calculation methods in problem solving.
  • Rigor and consistency in the development of mathematical reasoning.
  • The ability to develop mathematical models of basic technical situations.
  • Accuracy in calculations and the correct interpretation of the results obtained.

Basic Bibliography: 

All of the books listed below are available at the La Salle Library.
Parts 1 and 2: Functions of multiple variables, Multiple integrals N. Piskunov, ``Cálculo diferencial e integral,´´ Ed. Montaner & Simon G.L. Bradley, K.J. Smith, ``Cálculo de varias variables,´´ Ed. Prentice Hall G.B. Thomas, R.L. Finney, ``Cálculo ´´ varias variables,´´ Ed. Addison Wesley Longman J. De Burgos, ``Cálculo infinitesimal de varias variables´´, Ed. Mc Graw Hill
Part 3: Probability and statistics L. Vicent, R. Villalbí, ``Probabilitat´´, available in PDF in the eStudy D.D. Wackerly, W. Mendenhall, R.L. Schaeffer, " Estadística matemática con aplicaciones." Ed. Math

Additional Material: 

1. Lliçons de Càlcul de Probabilitats. Marta Sanz. 1995.Publicacions Universitat de Barcelona.
2. Problemas de Probabilidades y Estadística. C.M. Cuadras. Ediciones PPU. 1990. Barcelona.
3. Problemas de Análisis Matemático. Bombal. Marín. Vera. Editorial AC, libros científicos y técnicos. Madrid.