Class Statistics II

This course deepens data analysis methods using SPSS, with a focus on statistical inference applied to the interpretation of samples and populations. It also covers the comparison of populations and the construction and application of linear regression models, fostering students' ability to analyze data and support decisions with evidence.

Not applicable

- Sampling and sampling distributions: Introduction. Central limit theorem. Distribution of: sample mean, difference of sample means, sample proportion, difference of sample sample proportions, sample variance and sample variance ratio.- Estimation: Introduction. Point and interval estimation.- Hypothesis testing: Introduction. Errors in hypothesis testing. P-value. Parametric tests. Analysis of variance. Non-parametric tests. Tests of and association tests. Kruskal-Wallis test.- Simple linear regression: Introduction. Simple linear regression model. Least squares method. method. Coefficient of determination. Model hypotheses. Tests of significance. Residual analysis. Application of the regression equation equation for estimation and forecasting.

Pedagogical practices will be mediated by I nformation and C ommunication T echnologies, using computers and/or mobile devices. Students will be exposed to interactive resources such as quizzes. Learning based on problem-solving will be promoted, in which students, guided by the teacher, will have to identify problems and plan and carry out ways of resolution. The aim is to improve the teaching and learning process and provide students with the necessary necessary competences for the challenges currently facing humanity and to increase their motivation towards the motivation in relation to the course.

- Afonso, A., e Nunes, C. (201 9 ). 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