Research Methodologies and Techniques

Code:

PDEMGEO23

Acronym:

MTI

Keywords
Classification	Keyword
OFICIAL	Mining and Geo-Resources Engineering

Instance: 2024/2025 - 1S

Active?	Yes
Responsible unit:	Department of Civil and Georesources Engineering
Course/CS Responsible:	Doctoral Program in Mining and Geo-Resources Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PDEMGR	3	Syllabus since 2009/2010	1	-	6	28	162

Teaching language

Portuguese and english

Objectives

At the end of this CU, the student must be able to develop and conduct experimental work (laboratory and/or otherwise) and/or research with other approaches, according to the research problem.

Learning outcomes and competences

Considering the research topic, the student should be able to resolve issues relating to the methodological approach in the most appropriate way. Whether they are questions of an experimental or conceptual nature, with a bias in its various aspects or even questions involving research ethics. In other words, the entire focus will be on a methodologically reproducible approach, which, through correct planning, will minimize efforts and resources throughout the entire investigation.

Working method

Presencial

Program

As the UC has a tutorial character the program is adapted to the research that the student will develop focussing on some of the following possible topics:

SAMPLING: Error, Heterogeneity - Constitution and Distribution; Processes; Plan; Types; Determination of the sample size; Variance of sampling; Incremental sampling.

ANALYSIS VARIANCE AND FACTORIAL PLAN OF TESTS: programming of research as control of variance: Factorial plan. Fractional plans; Central and centered composite plan; Factorial plan at three or more levels; signification analysis; mathematical model. Plackett and Burman method for screening variables.

SEQUENTIAL DATA ANALYSIS: Correlation Analysis, Confidence Limits (Regression Straight and Parameters). Monovariable Regression Analysis by Linearizing Transformation; Multivariate Linear Regression Analysis. Linearizable Multivariable Regressions, Splines, Markov Chains, Stochastic Process, Markov Chains in a Discrete State Space.

Mandatory literature

- Pierre, G; Hétérogénéité échantillonnage homogénéisation, 1988
John C. Davis; Statistics and data analysis in geology. ISBN: 0-471-83743-1
William G. Cochran; Experimental designs. ISBN: 0-471-54567-8
Oliver Schabenberger; Statistical methods for spatial data analysis. ISBN: 1-58488-322-7

Teaching methods and learning activities

In a previous meeting between the CU professors, the supervisor and the student, the theme of the work and the objectives are defined. The fundamental bibliography is also recommended to the student.

The CU professors who will monitor the students throughout the semester. There will be regular presentations to peers and CU professors. Advisors will also be invited to attend presentations by all students.

The student must include in their work, in addition to the specific development of all content to demonstrate that they have effective conceptual and methodological mastery of their research area, the following points: reflective analysis on the selected work, definition of the research problem and planning about its realization with due justifications.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	30,00
Trabalho escrito	70,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	4,00
Estudo autónomo	98,00
Frequência das aulas	14,00
Trabalho escrito	46,00
Total:	162,00

Eligibility for exams

Attendance at tutorial meetings and work presentation sessions.

Calculation formula of final grade

Student performance and participation throughout the semester will correspond to 30% and the written report to 70% of the final grade.

Examinations or Special Assignments

n.a.

Internship work/project

n.a.

Special assessment (TE, DA, ...)

n.a.

Classification improvement

n.a.