At the end of this course the students should:
1. Understand the concept of sampling distribution and to explain Central Limit Theorem
2. Identify the distribution of the main sample distributions
3. Explain the impact of sample size in the sampling distribution
4. Set confidence interval (CI) and confidence level
5. Build and interpret CI
6. Calculate the sample size given point estimate precision
7. Formulate assumptions of statistical tests and decide based on the appropriate test
8. Explain the two types of error and the power of the test
9. Calculate and interpret the p-value
10. State the assumptions and hypotheses ANOVA, calculate the ANOVA table and apply the F test
11. Apply multiple comparison tests
12. Distinguish parametric and non-parametric tests
13. Explain the procedures of the main non-parametric tests
14. Apply non-parametric tests
15. Describe the main sampling methods
16. Discuss sources of bias in sampling studies
Ana Cristina Marinho da Costa, Isabel Cristina Maciel Natário
Weekly - Available soon
Total - 61
Basic notions of Analysis and intermediate level notions of Probability.
Afonso, A., Nunes, C. (2011). Estatística e Probabilidades. Aplicações e Soluções em SPSS, Escolar Editora.
Bento Murteira, Marília Antunes, Probabilidades e Estatística Vol 1, Escolar Editora.
Ana Maria Lima de Farias, Inferência Estatística, Departamento de Estatística, UNIVERSIDADE FEDERAL FLUMINENSE, INSTITUTO DE MATEMÁTICA. Livro electrónico.
Conover, W. J. (1999). Practical nonparametric statistics. 3rd Edition, Wiley.
The curricular unit is divided into 7 topics that include lectures and videos of oral exposition of the contents, along with the presentation of examples and complemented by solved proposed exercises. At the end of each topic a revising exercise is delivered. During the curricular unit the students will present one evaluation assignment, contributing for the final grading. A timetable for explaining doubts to students made is available.
Evaluation: exam (30%) and assignment (70%)
1 - Sampling distributions and confidence intervals
2 - Hypothesis testing
3 - Inference for two samples
4 - bivariate analysis
5 - ANOVA
6 - nonparametric statistics
7 - Introduction to sampling theory
Programs where the course is taught: