Applied Statistics
| Keywords |
| Classification |
Keyword |
| OFICIAL |
Applied Mathematics |
Instance: 2006/2007 - 1T
Cycles of Study/Courses
Teaching language
Portuguese
Objectives
1) Give to the students the knowledge of statistical techniques that can extract the most important from multivariate data bases. The access to big data bases which contain important information is nowadays easy and cheap. The data analysis techniques have an important role in the transformation of these data in useful knowledge to make decisions.
2) Give same knowledge about sampling theory.
Program
1) Statistic as Science
2) Data Analysis
2.1) Types of data
2.2) Data organization
2.3) Summarizing univariate and bivariate data
2.4) Outliers and missing values
3) Multivariate Data Analysis
3.1) Factorial Methods
3.1.1) Principal Component Analysis
3.1.2) Simple Correspondence Analysis
3.1.3) Multiple Correspondence Analysis
3.2) Cluster Analysis
3.2.1) Non Hierarchical Classification
3.2.2) Hierarchical Classification
3.2.3) Discriminant Analysis
4) Sampling Techniques
4.1) Sampling empiric methods
4.2) Sampling probabilistic methods
Mandatory literature
Maroco, João;
Análise estatística. ISBN: 972-618-298-0
Saporta, Gilbert;
Probabilités analyse des données et statistique. ISBN: 2-7108-0565-0
Complementary Bibliography
Diday, Edwin 070;
Éléments d.analyse de données. ISBN: 2-04-015430-2
Teaching methods and learning activities
Expository classes, with the presentation of the studied concepts and methods, using the geometrical interpretation and also examples. Big appeal to the motivation of the methods and comprehension of the concepts. During the classes, students are informed about the capacities and restrictions of the software available on this field.
Evaluation Type
Distributed evaluation with final exam
Assessment Components
| Description |
Type |
Time (hours) |
Weight (%) |
End date |
| Attendance (estimated) |
Participação presencial |
30,00 |
|
|
|
Total: |
- |
0,00 |
|
Calculation formula of final grade
Practical Work (PW) - 5 values
Final Examination (FE) - 15 values
Final Classification (FC) = PW + FE
Classification improvement
As in Master course rules.