Course Unit Code | 114-0575/01 |
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Number of ECTS Credits Allocated | 3 ECTS credits |
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Type of Course Unit * | Choice-compulsory |
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Level of Course Unit * | First Cycle, Second Cycle |
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Year of Study * | |
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Semester when the Course Unit is delivered | Winter Semester |
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Mode of Delivery | Face-to-face |
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Language of Instruction | English |
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Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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Name of Lecturer(s) | Personal ID | Name |
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| AND0096 | doc. Antonio Rodríguez Andrés, Ph.D. |
Summary |
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Course contents includes the basics of R, pre-processing and data visualization techniques, study and application of linear, non-linear models, and basic panel data models. Students will apply and analyze the results using the R software. The student will prepare and present both in oral and written form a research project in which the concepts studied will be discussed and applied to a particular problem. |
Learning Outcomes of the Course Unit |
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Passing the course, student will be able to work with important basics of the descriptive analysis and statistics, data visualization, regression analysis, binary choice models, count and panel data models using statistical software R. |
Course Contents |
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Recommended or Required Reading |
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Required Reading: |
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LANDER, Jared P. [i]R for everyone: Advanced Analytics and Graphics.[/i] Crawfordsville: Adison Wesley, 2014. ISBN-13: 978-0-321-88803-7.
VERZANI, John. [i]Using R for introductory statistics.[/i] [online]. Available from: https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf.
WOOLDRIDGE, Jeffrey M. [i]Introductory econometrics: a modern approach. [/i] Sixth edition. Boston: Cengage Learning, 2016. ISBN 978-1-305-27010-7.
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Recommended Reading: |
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DOUGHERTY, Christopher. [i]Introduction to econometrics. [/i] Fifth edition. Oxford: Oxford University Press, 2016. ISBN 978-0-19-967682-8.
JAMES, G., D. WITTEN, T. HASTIE and R. TIBSHIRANI. [i]An Introduction to Statistical Learning Applications in R. [/i] Stanford: Springer, 2012. Available from: http://www-stat.stanford.edu/~tibs/.
NEUSSER, Klaus. [i]Time series econometrics.[/i] Switzerland: Springer, 2016. Springer texts in business and economics. ISBN 978-3-319-32861-4.
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Planned learning activities and teaching methods |
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Lectures, Individual consultations |
Assesment methods and criteria |
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Tasks are not Defined |