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Quantitative Methods

Code 13729
Year 1
Semester S2
ECTS Credits 4
Workload TP(45H)
Scientific area Mathematics
Entry requirements Basic notions of vectorial calculus, trigonometry, derivatives, and statistic.
Mode of delivery Face-to-face
Learning outcomes (i) Develop the capacity of reasoning and demonstration that will be useful in their academic career;
(ii) Provide students with fundamental skills they need for the disciplines of Applied Statistics, Biomechanics and Economics;
(iii) Applies the activities related to teaching and teaching basic skills required for the teaching of Physical Education;

Specific objectives:
- Operate with vectors
- Calculate the inner product and the cross product of vectors
- Determine the restoration search tangent to a curve at a point
- Apply derivation rules
- Calculate antiderivatives of some functions
- Apply the main theorem of integral calculus.
- Recognize various types and data
- Build bar diagrams, pie charts, and histograms
- Apply some measures of central tendency and dispersion

Syllabus Module I – Notions of vector calculus: Free vectors; Coordinates;scalar addition and multiplication, inner product, outer product and mixed product; Orthogonality and norm.
Module II – Calculation of derivatives: Derivative of a function at a point and derivative function; Geometric interpretation of the concept of derivative: Derivative as the slope of a straight line; The function derived from polynomial functions and some rational and irrational functions; Speed and prosperity as derivatives of functions.
Module III – Primitives and integral design in R: Immediate Primitivation; Integral calculus: geometric interpretation; Fundamental theorem of integral calculus;
Module IV – General notions of statistics: Statistical variables and measurement scales; General notions of sampling theory.
Module V – Descriptive statistics: Types of data (qualitative and quantitative); Frequency distributions; Bar diagrams, pie charts, histograms; Measurements; Measures of central tendecy
Main Bibliography Grieve, S. (2017). Mathematics in sport.

Guimarães, R., & Cabral, J. (2007). Estatística. McGraw-Hill.

Martins, R. (2007). Isto é Matemática - Como a FIFA mede as suas bolas.

Murteira, B. (1993). Análise Exploratória de Dados -- Estatística Descritiva. McGraw-Hill.

Pedrosa, A., & Gama, S. (2016). Introdução computacional à Probabilidade e Estatística. Porto Editora.

Pestana, D., & Velosa, S. (2002). Introdução à Probabilidade e à Estatística. Fundação Calouste Gulbenkian.

Stewart, J. (2013). Cálculo, Volume 1. Cengage.

Stewart, J. (2013). Cálculo, Volume 2. Cengage.
Teaching Methodologies and Assessment Criteria The typology of the classes will have a theoretical-practical nature. The theoretical contents exposed will be applied to the sporting context, as well as the respective applications. Worksheets will be solved, with the support of the teacher. The evaluation of this UC will be done as follows: 3 tests.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2024-03-13

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