Class Data Analysis I

The main goal of the curricular unit is to introduce students to descriptive statistics, probabilities and random variables. The syllabus was chosen taking into account the studies’ cycle framework and the syllabus of other curricular units, so that students can continue their studies and develop their professional activity.

Not applicable

- Descriptive statistics: Introduction. Population and sample. Parameters and statistics. Variables and their classification. Tables and graphics for univariate and bivariate data. Descriptive measures. Introduction to SPSS.   - Probabilities: Introduction. Random experiment, sample space and events. Probability: definition, interpretations and properties. Conditional probability. Independent events. Bayes' theorem.   - Random variables: Introduction. Discrete random variables. Probability function and distribution function. Continuous random variables. Probability density function and distribution function. Models of discrete and continuous random variables.

Classes are of theoretical and practical nature, where the theoretical exposition of the syllabus is accompanied by the presentation of practical examples and exercises. The evaluation is carried out taking into account the assessment regulation “Regulamento Geral de Avaliação da Universidade Lusófona”.   Pedagogical innovation practices: Pedagogical practices will be mediated by Information and Communication Technologies, using computers and/or mobile devices. Students will be exposed to interactive educational resources, such as quizzes. Problem-based learning will be promoted, where the students, guided by the teacher, should identify problems and plan and carry out resolution paths. The aim is to improve the teaching and learning process, to provide students with the necessary skills for the challenges that humanity currently faces and to increase their motivation regarding the studies’ cycle.

- Afonso, A., e Nunes, C. (2019). Probabilidades e Estatística: Aplicações e Soluções em SPSS - Versão revista e aumentada. Universidade de Évora.   - Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., e Cochran, J. J. (2019). Statistics for Business & Economics (14th edition). Cengage Learning.   - Pestana, M. H., e Gageiro, J. N. (2014). Análise de Dados para Ciências Sociais - A Complementaridade do SPSS (6ª edição). Edições Sílabo.