Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (16.09.2022)
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: prof. PhDr. Ladislav Krištoufek, Ph.D. (19.09.2022)
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.
Cíl předmětu -
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (16.09.2022)
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: prof. PhDr. Ladislav Krištoufek, Ph.D. (19.09.2022)
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.
Literatura -
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (16.09.2022)
Kabacoff, Robert I. (2015): R in Action (2E), Manning Publications, Shelter Island, NY
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (19.09.2022)
Kabacoff, Robert I. (2015): R in Action (2E), Manning Publications, Shelter Island, NY
Metody výuky -
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (06.10.2023)
Please switch to the English version.
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (05.10.2023)
Combination of online (pre-recorded) lectures and in-person group consultations. The group consultations will take place in room 016 on 27 Oct (Week 4), 10 Nov (Week 6), 24 Nov (Week 8), 8 Dec (Week 10), and 22 Dec (Week 12) between 11:00 and 12:30., and they will be led by Anna Drahozalova, the TA of the course. Please direct your questions for consultations to her, ideally some time ahead.
Software: R a RStudio (available on all computers in room 016), available here a here (freeware).
Požadavky ke zkoušce -
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (06.10.2023)
Please switch to the English version.
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (02.10.2023)
There are two components to the final score and grade:
3 tracks in DataCamp (35 points)
4 assessments in DataCamp (65 points)
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 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" (7.5 points) - by 19 November 2023 CEST
Track 2: Skill Track "Importing & Cleaning Data" (7.5 points) - by 10 December 2023 CET
Track 3: Career Track "Data Analyst with R" (20 points) - by 4 February 2024 CET
Assessments (upload a printscreen of your finished assessments to the Study Roster, make sure you name is visible in the printscreen):
Assessment 0: Understanding and Interpreting Data (5 points) - by 5 November CEST
Assessment 1: R Programming (20 points) - by 19 November 2023 CEST
Assessment 2: Importing & Cleaning Data with R (20 points) - by 10 December 2023 CET
Assessment 3: Data Manipulation with R (20 points) - by 4 February 2024 CET
Scoring:
For Assessment 0, you need to get at least 120 score in DataCamp to pass and obtain 5 points.
For Assessments 1-3:
To get the score, use the DataCamp score x and fit it to (x-60)/80*100%
At least 50%, i.e. at least 10 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).
Grading scale follows the faculty regulations:
A: 90+
B: 80-90
C: 70-80
D: 60-70
E: 50-60
F: below 50
Sylabus -
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (06.10.2023)
Please switch to the English version.
Poslední úprava: prof. PhDr. Ladislav Krištoufek, Ph.D. (26.12.2023)
