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.

General characterization





Responsible teacher

Jorge Ricardo da Costa Ferreira


Weekly - 4

Total - 168

Teaching language





Dadson., S. (2017). Statistical Analysis of Geographical Data: An Introduction.Wiley-Blackwell; 1st edition.
Dixson, T. (2021). Urban Futures: Planning for City Foresight and City Visions. 1st Edition. Policy Press, Reading University.
Marôco, J. (2021). Análise Estatística com o SPSS Statistics. (8ª Edição).Editora Report number.
Pestana, M. & Gageiro, J. (2017) Análise de dados para Ciências Sociais, A complementaridade do SPSS (7ª edição). Lisboa: Edições Silabo.
Vários autores. Textos de apoio sobre Prospetiva estratégica, prospetiva territorial e Cenários.

Teaching method

Expository and participatory classes (theoretical and practical in the same proportion).
In relation to inferential statistics, emphasis is placed on the explanation and elaboration of exercises ("handmade" and by statistical software). Knowledge about a statistical software package for geographic analysis will also be considered as a variable for evaluation.
Regarding the Prospective subjects, a practical work will be prepared in the context of a project, having as a starting point the set of syllabus related to this subject, but focused on the resolution of a practical case.

Evaluation method

Evaluation Methodologies - Written assessment(60%), and practical assignment(s). These ratings percentages may be subject to change due to Contingency Plans caused by the Covid-19 pandemic.(40%)

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.


Programs where the course is taught: