Class Data Analysis II

The main goal of the curricular unit is to introduce students to statistical inference techniques and to linear regression. 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

- Sampling and sampling distributions: Introduction. Central limit theorem. Distribution of: sample mean, difference between sample means, sample proportion, difference between sample proportions, sample variance and ratio of sample variances.   - Estimation: Introduction. Point and interval estimation.   - Hypothesis testing: Introduction. Errors in hypothesis testing. p-value. Parametric tests. One-way analysis of variance. Non-parametric tests. Goodness of fit and association tests. Kruskal-Wallis test.   - Simple linear regression: Introduction. Simple linear regression model. Least squares method. Coefficient of determination. Model assumptions. Significance tests. Residual analysis. Application of the estimated regression equation for estimation and prediction.

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.

Marôco, J. (2024). Fundamentos de Estatística. ReportNumber. Newbold, P., Carlson, W. L., & Thorne, B. M. (2019). Statistics for business and economics: Global edition (13rd ed.). Pearson.