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Teaching GuideTerm Higher Polytechnic University College |
| Master Universitario Erasmus Mundus en Sostibilidade e Industria 4.0 aplicada ao Sector Marítimo |
 Subjects |
| Statistical Models for Marine Technology Innovation |
| Contents |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Statistical Models for Marine Technology Innovation | Code | 730542016 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 6 | ||||||||||
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| Topic | Sub-topic |
| Multivariate data description and inference. |
Exploratory analysis of multivariate data. Statistical inference of multivariate data. Introduction to R statistical software. |
| Elements of unsupervised learning. |
Principal component analysis (PCA). Unsupervised clustering or classification methods. |
| Elements of supervised learning. |
Multivariate linear regression models. |
| Selection, regularization of linear models and dimension reduction methods. |
Ridge regression. Least absolute shrinkage and selection operator (LASSO). Principal component regression. Partial least squares (PLS) regression. |
| Classification methods. |
Introduction. Supervised classification methods. |
| Statistical Process Control (SPC). |
Control charts of variables and attributes. Hotelling's T2 control chart. Regression adjustment. Interpretation of out-of-control signals. |
| Case studies to be solved using R statistical software. |
Case studies in the field of naval and maritime engineering. |
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