| Código |
13129
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| Ano |
2
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| Semestre |
S2
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| Créditos ECTS |
6
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| Carga Horária |
TP(60H)
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| Área Científica |
Sociologia
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Mode of delivery |
Presential classes
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Learning outcomes |
The student must be able to get a sample, briefly describe the sample data, perform statistical inference using parametric hypothesis testing. Finally, must be able to model variables presenting the predictive model(s) and examine the significance of the model and its coefficients.
The student after attending this UC will be able to get a sample and carry out a project, briefly describe the sample data, perform statistical inference using parametric hypothesis testing. Finally, must be able to model the variables through predictive models and examine the significance of the model and its coefficients. All objectives should also be achieved using the computer program SPSS.
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Syllabus |
-Point Estimation, properties of estimators and estimation methods
- Interval estimation
Confidence interval for the mean, for the difference of means and for the proportion
- Hypothesis Tests
Errors, decision rules and significance level
TH for the mean, for the difference of two means, for the proportion and for paired samples
-Single and double variance analysis
Multiple Comparison Tests and Test of Homogeneity of Variances
-Non-parametric tests: chi-square, ordinal correlation of Spearman, Mann-Whitney, Wilcoxon and Kruskal-Wallis
- Simple linear regression
Assumptions, least squares estimators
Explanatory capacity of the model and coefficient of determination
Statistical inference and prediction
- Multiple linear regression
Examples in SPSS
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Teaching Methodologies and Assessment Criteria |
The assessment of this course unit will be conducted as follows: two knowledge assessment tests and one project. The tests will follow a mixed format (multiple-choice and written responses), allowing students to demonstrate their understanding of the mathematical concepts. The project will be developed using a digital tool, aiming to deepen the knowledge acquired during the theoretical lectures and to foster critical skills in the use of such tools in an educational context. This methodology combines theoretical mastery with practical competencies essential for the critical and effective integration of emerging technologies in the educational process.
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Main Bibliography |
Coelho, J.P., Martins I.L. & Cunha L.M. (2009) - Inferência Estatística com Utilização do SPSS e G*power, Ed. Silabo
- Ferreira, Sandra S. (2025). Apontamentos de Análise de Dados Quantitativos. Departamento de Matemática, UBI.
Guimarães, R. & Sarsfield Cabral, J.A. (1999)- Estatística - Editora McGraw-Hill Maroco, J. (2007) – Análise Estatística com utilização do SPSS - 3ª ed., Ed. Silabo
Muijs, D. (2011). Doing quantitative research in education with SPSS (2nd ed.). SAGE Publications Ltd
Santos, C. (2010) – Estatística Descritiva: Manual de auto-aprendizagem - 2ª ed., Ed. Silabo
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| Language |
Portuguese. Tutorial support is available in English.
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