Statistical Methods

Code:

EMG0020

Acronym:

ME

Keywords
Classification	Keyword
OFICIAL	Physical Sciences (Mathematics)

Instance: 2024/2025 - 2S

Active?	Yes
Responsible unit:	Mining Engineering Department
Course/CS Responsible:	Bachelor in Mining and Geo-Environmental Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.EA	62	Syllabus	2	-	6	52	162
L.EMG	22	Plano de estudos oficial a partir de 2008/09	2	-	6	52	162

Teaching language

Portuguese

Objectives

This UC aims to develop in students the ability to communicate accurate when referring to subjects that are based on concepts of Probability and Statistics. This UC also intends to develop a critical attitude when necessary to the analysis of statistical problems as well as the ability to apply the concepts acquired solving them. The acquisition of fundamental knowledge will give students the ability to acquire more advanced concepts that arise in the course and / or professional.

 

The scientific component is 100%.

Learning outcomes and competences

At the end students should be able to:

- Solving common problems involving probability theory, random variables, distributions, sampling, interval estimation and hypothesis testing for parametric and non-parametric;

- Formulate and interpret the key concepts of statistics;

- Using the tools of descriptive statistical analysis of sample data or population.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

NA

Program

1. Brief review of concepts:

- Combinatorial Analysis;

- Theory sets.

2. Probability theory: events and probabilities, concepts definitions and applications.

3. Random variable: discrete and continuous variables, functions and probability distribution parameters, sums and n-dimensional distributions.

4. Distributions: Distributions theoretical discrete and continuous approximations and sums.

5. Descriptive Statistics: Sampling. Analysis, graphical representations, parameters and distribution of measurements;

6. Estimation: Point and interval estimators for normal populations and not normal (central limit theorem and Tchebycheff inequality.

7. Hypothesis testing: Hypothesis testing parametric normal and non-normal populations.

8. Chi-square: independence and homogeneity adjustment.

9. Regression analysis and correlation.

10. Statistical data analysis using Microsoft Excel.

Mandatory literature

A bibliografia de referência básica e obrigatória é fornecida pelo docente
Pestana, Dinis Duarte e Velosa, Sílvio Filipe; Introdução à Probabilidade e à Estatística, Fundação Calouste Gulbenkian, 2002

Complementary Bibliography

Ventsell; Théorie des probabilités, Editions Mir
Mood, Alexander M.; Introduction to the theory of statistics. ISBN: 0-07-042864-6
Athanasios Papoulis; Probability, random variables, and stochastic processes. ISBN: 0-07-100870-5
Rui Campos Guimarães, José A. Sarsfield Cabral; Estatística. ISBN: 978-84-481-5589-6
Paul L. Meyer; Probabilidade. ISBN: 85-216-0294-4
Malik e Mullen; A first course in probability and statistics, , Addison-Wesley
Douglas C. Montgomery, George C. Runger; Estatística aplicada e probabilidade para engenheiros. ISBN: 85-216-1360-1
Murteira, Bento José Ferreira; Probabilidades e estatística. ISBN: 972-9241-17-1

Teaching methods and learning activities

In class concepts are presented and important results associated with an emphasis on geometric interpretations and practical applications. In order to clarify the definitions and theorems presented, several exercises are solved and illustrative applications are presented. The aim is to, whenever possible, the participation of students, not only in solving the exercises, but also in introducing new concepts. It remains to enhance the resolution of individual exercises and the guidance should be in the study of discipline and clarify questions that may arise in proposal exercises.

keywords

Physical sciences > Mathematics > Statistics
Physical sciences > Mathematics > Probability theory

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	60,00
Teste	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	106,00
Frequência das aulas	56,00
Total:	162,00

Eligibility for exams

Gets UC to this frequency, the current school year, every student: - Regularly enrolled in UC and does not exceed the maximum number of absences. 

Calculation formula of final grade

Regarding the assessment there are three distinct stages:

1) Test and Final Examination;

2) Examination Appeal.

 

The final match of the course (0-20):

- Arithmetic mean of the tests;
or
- The classification of exam.

Examinations or Special Assignments

NA

Internship work/project

NA

Special assessment (TE, DA, ...)

Students who are under special statutes or having the or who have had previous years frequency, are exempt frequency. The approval can be obtained by performing the tests or the exam resource (R), the final classification is done according to the previous point.

Classification improvement

Students wishing to undertake improvement of classification may submit the evaluation defined for the UC according with existing regulations.

Observations

Language of instruction: Portuguese