156-0557/03 – Economic analysis with R (EAR)

Gurantor departmentDepartment of National EconomyCredits4
Subject guarantordoc. Antonio Rodríguez Andrés, Ph.D.Subject version guarantordoc. Antonio Rodríguez Andrés, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory type B
Year2Semesterwinter
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
AND0096 doc. Antonio Rodríguez Andrés, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+3

Subject aims expressed by acquired skills and competences

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.

Teaching methods

Lectures
Tutorials

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.

Compulsory literature:

LANDER, Jared P. (2014). R for everyone: Advanced Analytics and Graphics. Crawfordsville: Adison Wesley, ISBN-13: 978-0-321-88803-7. VERZANI, J. (2002). Using R for introductory statistics. Available at https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf.

Recommended literature:

JAMES, G., D. WITTEN, T. HASTIE and R. TIBSHIRANI (2012). An Introduction to Statistical Learning Applications in R. Springer. 2nd edition. Available at http://www-stat.stanford.edu/~tibs/.

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

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Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit Credit 100  51
Mandatory attendence parzicipation: Conditions stated by lecturer.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N0311A050012) Applied economics (S01) International Economic Relations P Czech Ostrava 2 Choice-compulsory type B study plan
2019/2020 (N0311A050013) Applied Economics (S02) International Economic Relations P English Ostrava 2 Choice-compulsory type B study plan
2019/2020 (N0311A050013) Applied Economics (S01) Economic Development P English Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner