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View general information Description The subject within the syllabus as a whole Learning objectives and results Content View the UOC learning resources used in the subject Additional information on bibliography and information sources Methodology Guidelines on assessment at the UOC View assessment model Continuous assessment | ||||||||||||||||||||||||
This is the course plan for the first semester of the academic year 2024/2025. To check whether the course is being run this semester, go to the Virtual Campus section More UOC / The University / Programmes of study section on Campus. Once teaching starts, you'll be able to find it in the classroom. The course plan may be subject to change. | ||||||||||||||||||||||||
One of the main objectives of this course is to obtain a good knowledge of some of the most relevant quantitative techniques, their advantages and disadvantages, their applicability according to the type of data and subjects of study, and their complementarity. With these techniques, we will do different activities by using different statistical packages (such as LISREL), discussing possible relationships of dependency or interdependence between variables. I hope it's useful in your research activity. Although it is a workshop, where we will apply each technique to specific cases, with real data, you will also have basic references in both web format and recommended bibliography, to understand the theoretical foundations of each technique. |
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This course complements the knowledge developed in previous quantitative courses of the Master's Degree in Information and Knowledge Society. | ||||||||||||||||||||||||
S1: Good knowledge of the most relevant quantitative and qualitative techniques, their advantages and disadvantages, their applicability according to the type of data and subjects of study and their complementarity. S2: Trained to determine the feasibility and reliability, strengths and weaknesses of different methods and techniques. S3: Awareness of the possibilities, opportunities and issues posed by empirical analysis of the Internet and other ICTs. S4: Mastering a statistical set that facilitates the application of statistical techniques, data analysis and drawing of conclusions. |
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1. Sampling methods
2. Topics in econometrics 3. Modelling Structural Equations (SEM)
4. Neural Networks (NN)
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Unit 1: Sampling methods
Unit 2: Topics in econometrics
Unit 3: Modeling Structural Equations (SEM)
Unit 4: Neural networks
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As part of the Wikipedia for higher education (https:In.Wikipedia.org/wiki/Higher_education), developed by a group of professors from both the Universitat Oberta de Catalunya (UOC) and the Universitat Politacnica de Catalunya (UPC), through this course we will actively use Viquipedia as a learning tool. Although Viquipedia is widely used by students, at any academic level, it is difficult to find Higher Education courses that are designed taking into account the great possibilities of this free encyclopaedia. The learning methodology of this course is based on the work that has to be carried out in each continuous evaluation activity. This continuous evaluation is a perfect strategy integrated into the learning process, conceived as a mechanism for learning and giving reciprocal feedback. This course is an applied course, and we will be especially interested in showing how each technique can be used to demonstrate different research hypotheses. There are 4 evaluation activities, one for each part of the course. To resolve the questions proposed in each activity, the student will have the following learning resources: 1. Theoretical part
2. Applied part
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The assessment process is based on the student's personal work and presupposes authenticity of authorship and originality of the exercises completed. Lack of authenticity of authorship or originality of assessment tests, copying or plagiarism, the fraudulent attempt to obtain a better academic result, collusion to copy or concealing or abetting copying, use of unauthorized material or devices during assessment, inter alia, are offences that may lead to serious academic or other sanctions. Firstly, you will fail the course (D/0) if you commit any of these offences when completing activities defined as assessable in the course plan, including the final tests. Offences considered to be misconduct include, among others, the use of unauthorized material or devices during the tests, such as social media or internet search engines, or the copying of text from external sources (internet, class notes, books, articles, other students' essays or tests, etc.) without including the corresponding reference. And secondly, the UOC's academic regulations state that any misconduct during assessment, in addition to leading to the student failing the course, may also lead to disciplinary procedures and sanctions. The UOC reserves the right to request that students identify themselves and/or provide evidence of the authorship of their work, throughout the assessment process, and by the means the UOC specifies (synchronous or asynchronous). For this purpose, the UOC may require students to use a microphone, webcam or other devices during the assessment process, and to make sure that they are working correctly. The checking of students' knowledge to verify authorship of their work will under no circumstances constitute a second assessment. |
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Weighting of marks
Option to pass the course: Continuous assessment
Final course mark: Continuous assessment |
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There are 4 evaluation activities, one for each part of the course. |