Úvodní kurz datové analytiky v prostředí R. Předmět uvádí do základního praktického programování v prostředí R, zahrnující datové struktury, práci s daty, grafické výstupy, základní statistiky, analýzu rozptylu, sílu testů, bootstrapping a komponentovou a faktorovou analýzu.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (16.09.2022)
An introductory course to data analysis in R. The course covers the basics of practical programming in the R environment, including data structures, data manipulation, graphs, graphical outputs, basic statistics, variance analysis, test powers, bootstrapping, and component and factor analysis.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (19.09.2022)
Cíl předmětu -
Cílem předmětu Data Analysis in R je poskytnout základnu pro analytickou práci s daty v komplementaritě s ostatními povinnými kurzy, jemnovitě Introductory Statistics, Statistics, Econometrics I a Econometrics II.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (16.09.2022)
The aim of Data Analysis in R is to lay foundations for analytical work with data complememtary to the other compulsory courses, namely Introductory Statistics, Statistics, and Econometrics I + II.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (19.09.2022)
Literatura -
Kabacoff, Robert I. (2015): R in Action (2E), Manning Publications, Shelter Island, NY
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (16.09.2022)
Kabacoff, Robert I. (2015): R in Action (2E), Manning Publications, Shelter Island, NY
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (19.09.2022)
Metody výuky -
Please switch to the English version.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (06.10.2023)
Traditional classes.Recordings of all classes are available online as well. Links to the videos are provided in the Syllabus section. The recordings are 1:1 with the standard classes.
Reschedulings:
11. 10. -> 18. 10. 12:30 (206, i.e. two classes in a row)
25. 10. -> 23. 10. 8:00 (314)
22. 11. -> 18. 11. 15:30 (314)
13. 12. -> 9. 12. 15:30 (314)
Software: R a RStudio (available on all computers in room 016), available here a here (freeware).
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (03.10.2024)
Požadavky ke zkoušce -
Please switch to the English version.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (06.10.2023)
There are 3 components to the final score and grade:
2 tracks in DataCamp (40 points)
3 assessments in DataCamp (30 points)
1 research report (30 points) (you can use this shared table to set up teams)
Use this LINK to register to DataCamp, fill in the profile (properly, use your name, it will be used to track fulfillment of assignments), and complete your assignments there. If you do not have a @fsv.cuni.cz/@cuni.cz/@.365.cuni.cz email, let me know, I will send you an invite.
Tracks (upload certificates of completion to the Study Roster, separately for the completed tracks):
Track 1: Skill Track "R Programming Fundamentals" (15 points) - by 10 November 2024 CEST
Track 2:Career Track "Data Analyst with R" (25 points) - by 26 January 2025 CET
Assessments (upload a printscreen of your finished assessments to the Study Roster, make sure you name is visible in the printscreen):
Assessment 1: Data Manipulation with R (10 points) - by 10 November 2024 CEST
Assessment 2: Statistics Fundamental in R (10 points) - by 1 December 2024 CET
Assessment 3: R Programming (10 points) - by 22 December 2024 CET
Scoring:
To get the score, use the DataCamp score x and fit it to (x-60)/80*100%
At least 50%, i.e. at least 5 points, from each assessment is a necessary (not a sufficient) condition for passing the Data Analysis in R course.
You can re-take the assessments twice a week during the whole semester. Remember that the last one counts (not necessarily the best one).
Research report (upload a zip file including the report, R code, and dataset, to the Study Roster):
Teams of up to 4 students.
Up to 8 pages (including everything but the code and data which will form separate attachments).
Submit by 2 February 2025 CET.
Grading scale follows the faculty regulations:
A: 90+
B: 80-90
C: 70-80
D: 60-70
E: 50-60
F: below 50
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (14.11.2024)
Sylabus -
Please switch to the English version.
Poslední úprava: Krištoufek Ladislav, prof. PhDr., Ph.D. (06.10.2023)
BLOCK I - GETTING STARTED:
Introduction to R and RStudio (Course info, R basics)