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ECTS Course Overview



Economic analysis with R

* Exchange students do not have to consider this information when selecting suitable courses for an exchange stay.

Course Unit Code156-0557/01
Number of ECTS Credits Allocated4 ECTS credits
Type of Course Unit *Choice-compulsory
Level of Course Unit *Second Cycle
Year of Study *
Semester when the Course Unit is deliveredWinter Semester
Mode of DeliveryFace-to-face
Language of InstructionEnglish
Prerequisites and Co-Requisites Course succeeds to compulsory courses of previous semester
Name of Lecturer(s)Personal IDName
AND0096doc. Antonio Rodríguez Andrés, Ph.D.
Summary
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
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
1. Getting R started: Downloading R, R version, Installing
2. The R Environment: Command line, and R studio
3. R packages: installing packages, loading packages
4. Basics of R: basic math, variables, missing data, vectors
5. Types of data: data frames, matrices, lists, and arrays
6. Reading data into R: Reading CSV files, reading Excel data, reading other datasets (Stata, and SPSS)
7. Basic graphs in R: the use of plot function
8. Advanced graphs using ggplot
9. Basic statistics: Summary statistics, covariance and correlation
10. Linear Models: Simple and multiple regression models
11. Generalized linear models: logistic models
12. Count data models: negative binomial and poisson models
13. Introduction to panel data: fixed and random effects models
14. Creating reports using R: The knitr command with R markdown
Recommended or Required Reading
Required Reading:
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.
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]. Dostupné z: 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.
Recommended Reading:
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.
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. Dostupné z: 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.
Planned learning activities and teaching methods
Lectures, Tutorials
Assesment methods and criteria
Tasks are not Defined