Inferential Analysis and Forecasting
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.
Jorge Ricardo da Costa Ferreira
Weekly - 4
Total - 168
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.
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.
second moment of evaluation in a form of exame or practical work(30%), an exame(70%)
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.
Programs where the course is taught: