| 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 evaluation of teaching learning (AE) will be composed as follows:
1 - TESTE - April 7th (13 values)
2 - Work - May 19th (7 values)
The final classification of teaching learning (CEA) results from the sum of
this two moments
Restrictions on admission to examination:
a) CEA <6 values;
b) Attendance: more than 34 hours
Students who obtain a classification greater than 17 values must submit to a supplementary test. In this test, the classification can be maintained or reduced, depending on the student's performance. If you do not attend, the minimum classification of 17 values will be ensured.
- Any reasoned suspicion of plagiarism / copy in the Frequencies / Worksheets / Exams will be punished with the classification of "NOT ADMITTED".
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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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