FSS:PSYb2320 R101: Practical introduction - Course Information
PSYb2320 R101: A practical guide to using R as your everyday statistical tool
Faculty of Social StudiesAutumn 2021
- Extent and Intensity
- 1/1/0. 4 credit(s). Type of Completion: z (credit).
- Teacher(s)
- Mgr. Karel Rečka (lecturer)
Mgr. Hynek Cígler, Ph.D. (lecturer)
doc. Mgr. Stanislav Ježek, Ph.D. (lecturer) - Guaranteed by
- doc. Mgr. Stanislav Ježek, Ph.D.
Department of Psychology – Faculty of Social Studies
Contact Person: Mgr. Karel Rečka
Supplier department: Department of Psychology – Faculty of Social Studies - Timetable
- Tue 18:00–19:40 U34
- Prerequisites
- Any introductory statistics course.
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 1/20, only registered: 0/20 - fields of study / plans the course is directly associated with
- there are 18 fields of study the course is directly associated with, display
- Course objectives
- The course has three main goals. The first is to weaken the dependence on paid statistical software that can be unavailable in many future workplaces of our students. The second is to spring interest in a programming language with vast analytical possibilities and a vital global community. The third goal is to refresh statistical foundations from previous courses students may have taken and expand it.
- Learning outcomes
- Student knows basic principles of the R language and classes of objects it manipulates. Student can work with data, filter it and transform. Student can perform basic statistical analyses and create graphical representations of data and statistics. Models include linear regression, logistic regression, factor analysis and confirmatory factor analysis.
- Syllabus
- R programming language, working with RStudio; creating and manipulating data objects; data import and cleaning; data description and exploration; data transformation; creating custom functions; iteration to reduce of duplicate code; dealing with missing data; power analysis; selected statistical models (e.g., correlations, linear regressions, hierarchical models); structural models (e.g., EFA, CFA, path analysis); reporting results.
- Literature
- required literature
- WICKHAM, Hadley and Garrett GROLEMUND. R for data science : import, tidy, transform, visualize, and model data. First edition. Sebastopol, CA: O'Reilly, 2016, xxv, 492. ISBN 9781491910399. info
- recommended literature
- GROLEMUND, Garrett. Hands-on programming with R : write your own functions and simulations. Edited by Hadley Wickham. 1st edition. Sebastopol: O'Reilly Media, 2014, xiii, 232. ISBN 9781449359010. info
- CHANG, Winston. R graphics cookbook : practical recipes for visualizing data. Second edition. Beijing: O'Reilly, 2019, xiii, 425. ISBN 9781491978603. info
- XIE, Yihui, J. J. ALLAIRE and Garrett GROLEMUND. R Markdown : the definitive guide. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2019, xxxiv, 303. ISBN 9781138359420. info
- BUUREN, S. van. Flexible imputation of missing data. Boca Raton, FL: CRC Press, 2012, xxv, 316. ISBN 9781439868249. info
- LITTLE, Todd D. Longitudinal structural equation modeling. Edited by Noel A. Card. London: Guilford Press, 2013, xxii, 386. ISBN 9781462510160. info
- Teaching methods
- lecture, seminar, online exercises, and discussion
- Assessment methods
- Credit awarded for individually evaluated online DataCamp exercises and presentation of an R package using R Markdown.
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
- Teacher's information
- https://www.datacamp.com/
This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Learn any time, anywhere and become an expert in R, Python, SQL, and more. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 350+ courses by expert instructors on topics such as importing data, data visualization, and machine learning. They’re constantly expanding their curriculum to keep up with the latest technology trends and to provide the best learning experience for all skill levels. Join over 6 million learners around the world and close your skills gap.
- Enrolment Statistics (Autumn 2021, recent)
- Permalink: https://is.muni.cz/course/fss/autumn2021/PSYb2320