It is recommended, although not compulsory, to have previously passed the subjects of Business Statistics and Statistical Inference and Introduction to Econometrics.
Nowadays, it is very frequent in the business world the availability of large volumes of data and the handling of computer tools that allow the adequate extraction of the information they contain. In this process, the knowledge and use of appropriate statistical techniques is fundamental to the discovery of new and significant relationships and patterns of behavior within the data. The objective of the course is to provide the student with the necessary tools for the representation, description and extraction of patterns and relationships between variables in multidimensional data, which is known in the statistical literature as "data mining".
Course competences | |
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Code | Description |
E07 | Understand the economic environment as a result and application of theoretical or formal representations on how the economy works. To do so, it will be necessary to be able to understand and use common handbooks, as well as articles and, in general, leading edge bibliography in the core subjects of the curriculum. |
E08 | Ability to produce financial information, relevant to the decision-making process. |
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 to use and develop information and communication technologies and to apply them to the corresponding business department by using specific programmes for these business areas. |
Course learning outcomes | |
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Description | |
Work out problems in creative and innovative ways. | |
Search for information in order to analyze it, interpret is meaning, synthesize it and communicate it to others. | |
Know the tools and methods for the quantitative analysis of the company and its environment, including models for business decision making as well as economic forecast models. | |
Know the analytical models and techniques of the economic and legal environment currently faced by enterprises, with special attention given to the search for opportunities and the anticipation of potential changes. | |
Additional outcomes | |
Description | |
Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | Description | |
Class Attendance (theory) [ON-SITE] | Lectures | E07 E08 G01 G03 G04 | 0.9 | 22.5 | N | N | Face-to-face lectures, in which the teacher will focus on the subject and explain its fundamental contents. | |
Class Attendance (practical) [ON-SITE] | Combination of methods | E07 E08 G01 G03 G04 | 0.9 | 22.5 | N | N | Classroom practice: exercises, seminars, debates. | |
Writing of reports or projects [OFF-SITE] | Group Work | E07 E08 G01 G03 G04 | 2 | 50 | Y | Y | Group workshops. At the beginning of the course, working groups will be created and a project will be assigned to them. The project will be developed throughout the course. | |
Other on-site activities [ON-SITE] | Combination of methods | E07 E08 G01 G03 G04 | 0.52 | 13 | Y | N | ||
Final test [ON-SITE] | Assessment tests | E07 G01 G04 | 0.08 | 2 | Y | Y | Preparation and performance of written test with questionnaire and exercises to be solved. | |
Study and Exam Preparation [OFF-SITE] | Self-study | E07 E08 G01 G04 | 1.6 | 40 | N | N | Student's autonomous work tutored by the teacher. | |
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 |
Fieldwork assessment | 50.00% | 0.00% | At the beginning of the course, working groups will be created and a project will be assigned to them, which will be developed throughout the course. These projects will be led by the teachers and can be displayed at the end of the course. |
Final test | 40.00% | 100.00% | Written test of a theoretical-practical nature. |
Assessment of active participation | 10.00% | 0.00% | The student's active participation in the classroom will be valued. |
Total: | 100.00% | 100.00% |
Not related to the syllabus/contents | |
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Hours | hours |
Writing of reports or projects [AUTÓNOMA][Group Work] | 50 |
Final test [PRESENCIAL][Assessment tests] | 2 |
Other on-site activities [PRESENCIAL][Combination of methods] | 13 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 40 |
Unit 1 (de 6): Introduction to Multivariate Analysis. The Multivariate Normal Distribution. | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 3 |
Unit 2 (de 6): Analysis of Variance | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 3 |
Unit 3 (de 6): Dimension Reduction Techniques. | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 4.5 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4.5 |
Unit 4 (de 6): Clustering Techniques | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 3 |
Unit 5 (de 6): Techniques for Qualitative Data Analysis | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 4.5 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4.5 |
Unit 6 (de 6): Other Techniques for Data Analysis in Business | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 4.5 |
Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4.5 |
Global activity | |
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Activities | hours |