Data Management and Organisation
Gestão e Organização de Dados
Course code:9548103
Luís Francisco Alexandrino Proença
Learning outcomes of the curricular unit:
- Formulate statistical hypotheses;
- Select and apply appropriate statistical methods based on data and problem characteristics;
- Interpret, discuss and recognize the limitations of statistical results;
- Correctly synthesize statistical information of various types;
- Understand and apply concepts of descriptive statistics and inferential statistical methods;
- Critically select the most appropriate statistical procedures and interpret the obtained results;
- Use specific software packages to perform statistical analysis;
Syllabus:
- Data organization. Fundamental concepts in statistics. Understanding inferential statistics.
- Descriptive statistics. Sample statistics (location, dispersion and shape). Outliers.
- Bivariate analysis. Variables crossing / association. Correlation analysis.
- Estimation of parameters. Random variables. Distributions. Confidence intervals.
- Hypothesis testing. Methodology of statistical analysis (assumptions, applicability conditions, test statistics, decision, errors). Statistical designs for research / tests application.
- Parametric tests. Validation of assumptions. Parametric analysis for independent and paired samples. Nonparametric tests. Non-parametric analysis for independent and paired samples.
- Regression analysis.
Suggested Bibliography:
- Callegari-Jacques SM (2003) Bioestatística: Princípios e Aplicações. Artmed. ISBN: 9788536300924.
- Dawson B, Trapp RG (2004) Bioestatística Básica e Clínica. McGraw-Hill. ISBN: 9788586804328.
- Marôco J (2011). Análise Estatística com o SPSS Statistics. ReportNumber. ISBN: 9789899676329.