13D081PS - Applied Statistics
| Course specification | ||||
|---|---|---|---|---|
| Course title | Applied Statistics | |||
| Acronym | 13D081PS | |||
| Study programme | Electrical Engineering and Computing | |||
| Module | ||||
| Type of study | doctoral studies | |||
| Lecturer (for classes) | ||||
| Lecturer/Associate (for practice) | ||||
| Lecturer/Associate (for OTC) | ||||
| ESPB | 9.0 | Status | elective | |
| Condition | Probability and Statistics course in undergraduate level (minimum 3 credits) | |||
| The goal | Knowledge acquisition about standard and specific methods in statistical methods in data analysis, with a view to applications. | |||
| The outcome | A student will be able to solve real problems using statistical procedures and software. | |||
| Contents | ||||
| Contents of lectures | Elements of data analysis. Measures of location and dispersion. Probability, random variables. Normal distribution. Correlation. Bayesian methods. Linear regression. Parameter estimation. Confidence intervals. Robust methods with multivariate data. | |||
| Contents of exercises | Study research work. | |||
| Literature | ||||
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| Number of hours per week during the semester/trimester/year | ||||
| Lectures | Exercises | OTC | Study and Research | Other classes |
| 6 | ||||
| Methods of teaching | Lecturing and consultations, study reaseach work. | |||
| Knowledge score (maximum points 100) | ||||
| Pre obligations | Points | Final exam | Points | |
| Activites during lectures | Test paper | 40 | ||
| Practical lessons | 60 | Oral examination | ||
| Projects | ||||
| Colloquia | ||||
| Seminars | ||||

