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 | ||||
| ||||
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 |