Degree | Type | Year |
---|---|---|
2503852 Applied Statistics | OB | 2 |
You can view this information at the end of this document.
It is recommended that the student have studied mathematics, statistics and linear models that have given him knowledge in linear algebra, matrix analysis, theory of probability and inference statistics (estimation and contrast of hypotheses).
The main objective of the course is to provide students with basic knowledge (theoretical and practical) of the econometric analysis of uniecuational models. The student will acquire the necessary capacity to perform the specification, estimation and contrast of applied econometric models and studies, as well as the ability to interpret general econometric results.
(T: theory, S: problems or seminars, PS: preparation of problems or seminars, L: laboratories, PP: practical preparation, E: study, AA: other activities, indicate the number of hours dedicated to each activity)
Unit 1: Introduction
Unit 2: The linear regression model
Estimate for Ordinary Least Squares
Contrasts
Prediction
Fictitious variables: application into testing structural change
Unit 3: Specification errors
Unit 4: Extension of the linear regression model
Unit 5: Dynamic Models
Regression analysis with time series
Distributed delay models
Unit 6: Models with discrete dependent variable
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Laboratory practices | 30 | 1.2 | |
Theory | 30 | 1.2 | |
Type: Supervised | |||
Solving problems | 30 | 1.2 | |
Type: Autonomous | |||
Study | 60 | 2.4 |
Two hours of theoretical classes a week plus two of practices (with econometric software) and resolution of exercises related to the contents explained in class in order to favor the assimilation of this knowledge by the student.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Delivery of Exercises and Empirical Work | 20% | 0 | 0 | KM17 |
Final exam | 40% | 0 | 0 | CM14, KM18 |
Practice Test | 20% | 0 | 0 | KM18 |
Written Test | 20% | 0 | 0 | SM16 |
The activities to evaluate the subject will be:
A student who has not participated in any of the described assessment activities will receive the "Not presented" qualification. If a student performs some of the assessment activities, even if it is only one, you can no longer opt for a "Not Presented".
In the case of failing the subject, the students will have the possibility of presenting themselves to a retake exam. In order to opt for this option it is essential to have submitted to both partial tests and to the final exam. The note of the retake exam replaces the note of the partial and the final exam. Therefore, notes on exercise deliveries and empirical work are not recoverable.
Attention: "Notwithstanding other disciplinary measures that are deemed opportune, and in accordance with the current academic regulations, the irregularities committed by the student who can lead to a variation of the qualification of an evaluation act will be graded with a zero. Therefore, plagiarizing, copying or letting copying a practice or any other evaluation activity will imply failing it with a zero and can not be recovered in the same academic year. If this activity has a minimum associated mark, then the subject will be failed. "
Lab practices will take place using R studio.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PLAB) Practical laboratories | 1 | Catalan | second semester | morning-mixed |
(PLAB) Practical laboratories | 2 | Catalan | second semester | morning-mixed |
(TE) Theory | 1 | Catalan | second semester | morning-mixed |