| Code |
15360
|
| Year |
2
|
| Semester |
S2
|
| ECTS Credits |
6
|
| Workload |
TP(60H)
|
| Scientific area |
Mathematics
|
|
Entry requirements |
Curricular Unit Probability and Statistics.
|
|
Mode of delivery |
Presential Classes
|
|
Learning outcomes |
The aim is to develop in students an intuitive understanding of Statistics and statistical reasoning, enabling them, when faced with an unfamiliar problem, to identify the appropriate statistical methods and tools to apply. Students are also expected to acquire practical experience in data analysis using statistical software, namely SPSS. They should be capable of structuring a database for statistical analysis; applying descriptive statistical methods and techniques to characterize a dataset; understanding and applying the main non-parametric tests; specifying, estimating, and interpreting simple and multiple linear regression models; and specifying, estimating, and interpreting analysis of variance models with one or more factors. In general, students should be able to participate in the conduct of statistical studies involving data processing and the interpretation of results.
|
|
Syllabus |
1. Non-Parametric Hypothesis Testing: runs test; Binomial test; Kolmogorov–Smirnov goodness-of-fit test; sign test; Wilcoxon signed-rank test; Mann–Whitney U test; two-sample Kolmogorov–Smirnov test; chi-square test; Fisher’s exact test.
2. Analysis of Variance (ANOVA): one-way ANOVA; two-way ANOVA with and without replication.
3. Simple Regression and Correlation: concepts of regression and covariance; least squares method; simple linear regression model; correlation coefficient; residual variance; coefficient of determination; fitting of non-linear models.
4. Multiple Regression and Correlation: multiple linear regression model; introduction to non-linear models.
|
|
Main Bibliography |
Gonçalves, E., Nogueira, E. e Rosa, A.C. (2016). {\it{Probabilidades e Estatística para Ciências e Tecnologia. Conceitos e exercícios resolvidos}}. Almedina. Cota: M-7.0-00028
Hall, A., Neves, C. e Pereira, A. (2011). Grande Maratona de Estatística no SPSS. Escolar Editora. Cota: EG-4.2-00500
Montgomery, D. e Runger, G. (2011). Applied statistics and probability for engineers, 5ª Edição, John Wiley \& Sons. Cota: MD-14-00531
Ross, S. (2009). Introduction to probability and statistics for engineers and scientists. Amsterdam Elsevier. Cota: F-1.8-01370 (CD)
|
|
Teaching Methodologies and Assessment Criteria |
The assessment of knowledge and skills acquired by students during the teaching-learning process is done by means of two tests (F_1 and F_2, rated from 0 to 20) with a weighting of 0.5 each.
The final teaching-learning classification (CEA,,expressed in 0 to 20 values) is calculated as follows
CEA=0,5F_1+0,5F_2,
Final exam exemption is granted when the CEA is equal to or higher than 9.5 points, requiring a minimum score of 3 points in each test and attendance of more than 80% of the classes. . The grade of ``FREQUENCY'' is awarded.when CEA is less than 9,5 points.
Grades above 18 points are defended with an oral exam.
|
|
Language |
Portuguese. Tutorial support is available in English.
|