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View general information Description The subject within the syllabus as a whole Professional fields to which it applies Prior knowledge Information prior to enrolment Content View the UOC learning resources used in the subject Additional information on support tools and learning resources Guidelines on assessment at the UOC View the assessment model | |||||
This is the course plan for the second semester of the academic year 2023/2024. 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. | |||||
This course is designed to provide the student with an integrated, in-depth but applied approach to multivariate data analysis. The course aims to provide students with a set of research tools that allow them to better analyze and understand the data from experiments where systems, networks or processes are analyzed and to satisfactorily explain the results obtained in scientific articles. Corresponding topics include, but are not limited to, the following: Multiple Regression, ANOVA, ANCOVA, Outlier Detection, Data Representation, Principal Component Analysis, Factor Analysis, Cluster Analysis. |
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This is an optional course for those interested in the study of multivariate data. |
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The course provides students with the necessary foundations of a data analyst. |
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It is advisable to have previous knowledge on linear algebra and programming. It is necessary to be able to read texts in English, although the book we follow is in Spanish. |
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Refer to the weekly-based planning |
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An introduction to R. | |||||
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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