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Lecturer(s)
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Fačevicová Kamila, Mgr. Ph.D.
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Course content
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1. R Markdown - Introduction 2. R Markdown - Static reports 3. R Markdown - Dynamic reports 4. R Markdown - Presentations 5. R Shiny - Introduction 6. R Shiny - Inputs 7. R Shiny - Outputs 8. R Shiny - Application Layout, publishing 9. Other related topics
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Learning activities and teaching methods
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Monologic Lecture(Interpretation, Training), Demonstration
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Learning outcomes
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The seminar is dedicated to non-analytical tools of the R software as R Shiny or R Markdown. Also other related topics will be discussed during the semester.
Ability of creating own R Shiny apps and R Markdown reports.
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Prerequisites
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Basic knowledge of the R language.
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Assessment methods and criteria
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Student performance, Final project
Preparation of an own statistical report and a Shiny app, presentation of results.
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Recommended literature
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Online manuál k R Markdown.
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Online manuál k R Shiny.
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Beeley, Ch. (2013). Web Application Development with R Using Shiny.
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Dabbas, E. (2021). Interactive Dashboards and Data Apps with Plotly and Dash: Harness the power of a fully fledged frontend web framework in Python - no JavaScript required.
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Wickham, H., Grolemund, G. (2017). R for Data Science. O´Reilly Media.
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Xie, Z., Allaire, J.J., Grolemund, G.: R Markdown. (2018). The Definitive Guide. Chapman and Hall/CRC The R Series.
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