2024
Data analysis and treatment in Geology
Name: Data analysis and treatment in Geology
Code: GEO13462M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Geology
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
This course is intended to deepen basic concepts and present the various tools available for displaying and extracting information from data.
With this course students should increase their ability to understand the literature on statistics and data analysis, becoming qualified to apply the analysis and processing of geological data independently.
Understand and apply solidly the ways of collecting, preparing geological data and presenting the results, being aware of both the uncertainties commonly associated with geological modelling and the multiple ways that data analysis and treatment offers to quantify such uncertainties.
With this course students should increase their ability to understand the literature on statistics and data analysis, becoming qualified to apply the analysis and processing of geological data independently.
Understand and apply solidly the ways of collecting, preparing geological data and presenting the results, being aware of both the uncertainties commonly associated with geological modelling and the multiple ways that data analysis and treatment offers to quantify such uncertainties.
Contents
Theoretical
1. Introduction
-Exploratory data analysis
-Anomalous and regional background
-Analysis of modeled data
2. Multivariate geochemical data
- Exploratory methods
-Limit elements and pathfinders
- Rejected data and acquisition problems
-Outliers; Robust estimation
-Transformation of data
3. Geochemical and geophysical data modeling
- Regression methods
-Classification analysis, principal component analysis
- D2 graphs: A multivariate extension of (qq) -plots
-Analysis of canonical variables
-Classifying unknown observations
4. Inversion problems
- Conceptualization
- Linear inverse problem
- Non-linear inverse problem
- Applications
5. Future Trends
Practice
1- Introduction to data analysis and processing software.
2- Data processing
3. Analysis and treatment of data applied to a case study
Preliminary data analysis
- Exploratory analysis of multivariate data
-Multivariate data modeling
-Inversion of data
1. Introduction
-Exploratory data analysis
-Anomalous and regional background
-Analysis of modeled data
2. Multivariate geochemical data
- Exploratory methods
-Limit elements and pathfinders
- Rejected data and acquisition problems
-Outliers; Robust estimation
-Transformation of data
3. Geochemical and geophysical data modeling
- Regression methods
-Classification analysis, principal component analysis
- D2 graphs: A multivariate extension of (qq) -plots
-Analysis of canonical variables
-Classifying unknown observations
4. Inversion problems
- Conceptualization
- Linear inverse problem
- Non-linear inverse problem
- Applications
5. Future Trends
Practice
1- Introduction to data analysis and processing software.
2- Data processing
3. Analysis and treatment of data applied to a case study
Preliminary data analysis
- Exploratory analysis of multivariate data
-Multivariate data modeling
-Inversion of data
Teaching Methods
The teaching will involve theoretical classes and above all theoretical practices in which students will learn the various approaches by solving real problems and analyzing scientific articles. Special emphasis will be given to the use of free software.
The classes will work through a "problem driven" methodology in which the students will try to solve, with the methodologies worked in the theoretical classes and theoretical-practical, real problems. Whenever possible the teaching will be done in the context of research that is under development in the Department of Geosciences.
The evaluation will have a continuous evaluation component (student involvement and availability, application of acquired knowledge, etc.), complemented by the evaluation of an article written about the case study and its poster presentation.
The classes will work through a "problem driven" methodology in which the students will try to solve, with the methodologies worked in the theoretical classes and theoretical-practical, real problems. Whenever possible the teaching will be done in the context of research that is under development in the Department of Geosciences.
The evaluation will have a continuous evaluation component (student involvement and availability, application of acquired knowledge, etc.), complemented by the evaluation of an article written about the case study and its poster presentation.
Teaching Staff (2023/2024 )
- Carlos Alexandre da Silva Ribeiro [responsible]
