It is recommended to have coursed the subject on Statistics for Economics
In the economic field, a basic management of the fundamental techniques for the treatment of quantitative information is essential. This need is translated into a knowledge of the main sources of statistical information, the basic rules for its interpretation and Analysis, and a mastery of the most relevant analytical-quantitative instruments. Therefore, the curriculum, within module 4 "Methods Quantitative for the Economy” devotes a section to the matter of Statistics, structured in two subjects: Statistics for Economics and Statistical Inference. The fundamental mission of the subject Inference Statistics is to deduce properties (make inferences) from a population, from a small part of it (sample). The goodness of these deductions is measured in probabilistic terms, that is, all inference is accompanied by its probability of success. Inferential statistics include: sample theory, estimation of parameters, hypothesis testing, experimental design and Bayesian Inference.
Course competences | |
---|---|
Code | Description |
E03 | Ability to find economic data and select relevant facts. |
E06 | Application of profesional criteria to the analysis of problems, based on the use of technical tools. |
E16 | Identify relevant sources of financial information and its content, as well as the ability to derive the important information from the data, otherwise completely unknown to non-professionals. |
G01 | Possession of the skills needed for continuous, self-led, independent learning, which will allow students to develop the learning abilities needed to undertake further study with a high degree of independence. |
G03 | Develop oral and written communication skills in order to prepare reports, research projects and business projects and defend them before any commission or group of professionals (specialised or non-specialised) in more than one language, by collecting relevant evidence and interpreting it appropriately so as to reach conclusions. |
G04 | Ability for the use and development of information and communication technology in the development of professional activity. |
G05 | Capacity for teamwork, to lead, direct, plan and supervise multidisciplinary and multicultural teams in both national and international environments. |
Course learning outcomes | |
---|---|
Description | |
Train the student to work out problems in creative and innovative ways. | |
Enable students to know the sources of official statistics and their treatment for the analysis of economic reality | |
To know the tools and methods for quantitative analysis of markets, sectors and companies, including models for decision-making and economic forecasting models. | |
Enable student for autonomous work and learning, as well as for personal initiative | |
Train the student to search for information in order to analyze it, interpret is meaning, synthesize it and communicate it to others. | |
Additional outcomes | |
Description | |
The student will be able to: a) Access the relevant statistical-economic information. B) Understand and apply the approximation of random variables, as a powerful tool to solve problems formed by the accumulation of infinity of small phenomena random. C) Extract a sample from a population with a level of randomness and representativeness sufficient to ensure the validity of the conclusions drawn. D) Identify the distribution of the phenomenon under study in a population and estimate their parameters (or characteristics) by the best possible procedures. E) Know how to identify a problem with the appropriate hypotheses and handle the corresponding techniques to test them. F) Recognize a problem, analyze it and solve it using the method scientific. G) Use basic software for statistical analysis (Excel and R) h) Solve problems in a creative and innovative way. I) Work and learn autonomously and with personal initiative. J) Collaborate with other students to achieve group work. K) Listen and defend oral and written arguments. |
Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | Description | |
Class Attendance (theory) [ON-SITE] | Lectures | E03 E06 E16 G01 G04 | 1.33 | 33.25 | N | N | The teacher will focus on the matter and the fundamental concepts. Time will also be dedicated for examples. | |
Class Attendance (practical) [ON-SITE] | Combination of methods | E03 E06 E16 G01 G03 G04 G05 | 0.67 | 16.75 | Y | N | Participation is valued | |
Study and Exam Preparation [OFF-SITE] | Self-study | E03 E06 E16 G01 G04 | 2.08 | 52 | Y | N | Independent work of student tutored by the teacher. | |
Writing of reports or projects [OFF-SITE] | Group Work | E03 E06 E16 G01 G03 G04 G05 | 0.72 | 18 | Y | N | At the beginning of the course working groups will be created and they handle a project that will develop along the course. These projects will be supervised by the teacher and may need to be exposed at the end of the course. | |
Other off-site activity [OFF-SITE] | Self-study | E16 G01 G03 G04 | 0.8 | 20 | Y | N | Individual practice. The teacher will provide the student some tasks which will have to be solved and delivered at the end of each theme. | |
Progress test [ON-SITE] | Assessment tests | E03 E06 E16 G01 G03 G04 | 0.04 | 1 | Y | N | Self evaluation tests | |
Final test [ON-SITE] | Assessment tests | E03 E06 E16 G01 G03 G04 | 0.08 | 2 | Y | Y | Test preparation and conduct written questionnaire and exercises to solve | |
Other on-site activities [ON-SITE] | Combination of methods | E03 E06 E16 G04 | 0.28 | 7 | N | N | Seminars or group tutorials | |
Total: | 6 | 150 | ||||||
Total credits of in-class work: 2.4 | Total class time hours: 60 | |||||||
Total credits of out of class work: 3.6 | Total hours of out of class work: 90 |
As: Assessable training activity Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).
Evaluation System | Continuous assessment | Non-continuous evaluation * | Description |
Assessment of active participation | 5.00% | 0.00% | The active attitude of the student will be assessed in the classroom. |
Assessment of problem solving and/or case studies | 20.00% | 0.00% | Throughout the course, three practices will be proposed for the resolution or, alternatively, the realization of a poject. |
Progress Tests | 10.00% | 0.00% | Written choice test with 10 questions. Each question has three alternative answers, one correct and two incorrect. Each correct answer adds 1 point and each failed subtract 0.5, questions left blank unscored. |
Final test | 65.00% | 100.00% | Written test with some practical questions to be solved |
Total: | 100.00% | 100.00% |
Not related to the syllabus/contents | |
---|---|
Hours | hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3.25 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 1.75 |
Progress test [PRESENCIAL][Assessment tests] | 1 |
Final test [PRESENCIAL][Assessment tests] | 2 |
Other on-site activities [PRESENCIAL][Combination of methods] | 7 |
Unit 1 (de 5): DISTRIBUTIONS DERIVED FROM THE NORMAL AND THE CENTRAL LIMIT THEOREM | |
---|---|
Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 5 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2.5 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 8 |
Other off-site activity [AUTÓNOMA][Self-study] | 3 |
Teaching period: 2.5 weeks |
Unit 2 (de 5): DISTRIBUTIONS IN SAMPLING | |
---|---|
Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 5 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2.5 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 8 |
Other off-site activity [AUTÓNOMA][Self-study] | 3 |
Teaching period: 2.5 weeks |
Unit 3 (de 5): ESTIMATORS AND THEIR PROPERTIES | |
---|---|
Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 8 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 15 |
Writing of reports or projects [AUTÓNOMA][Group Work] | 2 |
Other off-site activity [AUTÓNOMA][Self-study] | 6 |
Teaching period: 4 weeks |
Unit 4 (de 5): HYPOTHESES TESTING | |
---|---|
Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 8 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 15 |
Writing of reports or projects [AUTÓNOMA][Group Work] | 8 |
Other off-site activity [AUTÓNOMA][Self-study] | 6 |
Teaching period: 4 weeks |
Unit 5 (de 5): ANALYSIS OF THE VARIANCE (ANOVA) | |
---|---|
Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 4 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 6 |
Writing of reports or projects [AUTÓNOMA][Group Work] | 8 |
Other off-site activity [AUTÓNOMA][Self-study] | 2 |
Teaching period: 2 weeks |
Global activity | |
---|---|
Activities | hours |
General comments about the planning: | Planning may vary depending on the schedule and teaching needs. |