Inferential Analysis and Forecasting - 2nd semester
Code
711041068
Academic unit
Faculdade de Ciências Sociais e Humanas
Department
Geografia e Planeamento Regional
Credits
6
Teacher in charge
Jorge Ricardo Ferreira
Weekly hours
4
Teaching language
Portuguese
Objectives
a) Analyze the theoretical foundations of statistical inference and recognize its limitations when faced with the society and territorial dynamics;
b) Differentiate methods and techniques of statistical inference in Geography, selecting the appropriate ones to the problems to be solved;
c) Interpret parametric and non-parametric tests for spatial data analysis;
d) Apply statistical analysis software (comercial and free software) to geographic data resulting from field work;
e) Plan the application of surveys and prepare an analysis of results;
f) Analyze the theoretical foundations of Foresight. Deepen concepts of strategic and territorial foresight;
g) Develop an attitude of rigor and precision in the application of methods and statistical techniques;
h) Apply with critical thinking, knowledge to real scenarios and adapting it to new situations.
Prerequisites
None.
Subject matter
1. Introduction to inferential analysis: objectives and concepts for geographic phenomena analysis;
2. Samples and populations: sampling theory and associated errors;
3. Estimation of a parameter. Definition of null hypothesis. Parametric and non-parametric tests;
4. Introduction to a statistical analysis software for processing and editing of geographic data (physical and human);
5. Surveys: concepts and methodologies for application in different contexts (spatial scales, types of survey, spatial referencing, quality control and validation);
6. Elaboration of a survey (digital platform) for planning, land use planning and decision support;
7. Introduction to Foresight: objectives and concepts for the analysis of geographic phenomena. Strategic foresight and territorial foresight: discussion of case studies;
8. Models for territorial analysis and predictive scenarios.
Bibliography
Clapez, T., Reis, E., Melo, P. & Andrade, R. (2007). Estatística Aplicada, Vol. 1 (159-355). Lisboa: Edições Sílabo.
D´Hainaut, L. (1997). Conceitos e Métodos da Estatística, Uma Variável a uma Dimensão, Vol. 1 (17-26). Tradução António Rodrigues Lopes. Lisboa: Fundação Calouste Gulbenkian e Serviço de Educação.
Patrício T. & Pereira, A. (2013). Análise de Dados com SPSS (8ª Edição). Lisboa: Edições Sílabo.
Pestana, M. & Gageiro, J. (2014) Análise de dados para Ciências Sociais, A complementaridade do SPSS (6ª edição). Lisboa: Edições Silabo.
Walford, N. (2002). Geographical Data: Characteristics and Sources. Chichester: Wiley.
Teaching method
Expository and participatory classes (theoretical and practical in the same proportion). Emphasis is given to the explanation and analysis of statistical exercices (\"hand made\" and by software). The reading of selected bibliography and knowledge about a statistical software package for geographic analysis will be taken as evaluation variables.
Evaluation method
The contents will be evaluated by: (i) an exame (weighting of 70% of final grade) and, (ii) a second moment of evaluation (weighting of 30%) in a form of exame or practical work. These percentages could vary depending on the student statute and will be communicated at the begining of each semester on the Moodle platform.
(According to the FCSH Assessment Standards, the proposed evaluation elements to introduce students in the first class may suffer readjustments, particularly in the percentage of each element).