PICO DEL VELETA, SIERRA NEVADA (3.394 M.) | Copyright © Matúš Maciak

(NMSA 407)   Linear regression

Lectures: doc. RNDr. Arnošt Komárek, Ph.D.

Lab sessions: Tu: 12:20 - 13:50 @K11 (lecturer: Stanislav Nagy)
Th: 14:00 - 15:30 @K11 (lecturer: Matúš Maciak)
Th: 15:40 - 17:10 @K4 (lecturer: Matúš Maciak)

General Information
Three 'parallel' sessions, all in English language, are taking place in the winter term 2020/2019. Each student attending one of these sessions is expected to be officially enrolled for the corresponding session in SIS. Any exceptions must be discussed and agreed with both lecturers. The sessions are synchronized in order to cover the same topics and mostly the content of the classes held in the same week will be approximately the same.

Due to the recent Covid-19 regulations the teaching procees will be based on online lectures (online video, supporting material, additional individual tasks, online discussion sessions). More details will be distributed by email (using the email addresses assigned to students in SIS). The students are, therefore, required to use their own computers/laptops and the statistical software R. If the Covid-19 regulations allow for in-person lectures the computers provided in the lecture rooms K4 and K11 (with the R software being already installed on all of them) can be used alternatively. Further details and most recent informations are also provided in Moodle UK. (login + enrollment key required) Students will obtain the Moodle login details after the registration. The enrollment key together with the group specific enrollment keys will be distributed by email.

Credit Requirements
The credit requirements for the NMSA407 exercises consist of two main parts.

More details about the credit requirements, the homework assignments, and the final test can be found in the NMSA 407 Credit Requirements document.

Syllabus & Script Files
The syllabus will be updated as the semester progresses. The R script files provided below will be discussed during the sessions and they will evaluated with the R software and explained correspondingly (with a focuss on the statistical theory behind, not the implementation of the R commands themselves). Thus, all students are expected to be familiar with R and to be able to handle R programming by themselves.

Supplementary Material
Supporting material -- audio/video recordings specific for each R script from the sylabus list -- will be avaiable at the given week on Moodle UK. Students need to register and they must be enrolled for the course.

Additional material (final test examples, a brief theory on the maximum likelihood estimation, etc.) can be found here.

Homework Assignments
There will be two homework assignments. Each homework assignment can be worked out in a group of 1--3 students and different groups can be formed for different homework assignments. Groups of three students are preferable. For more details about the homework assignments see the NMSA 407 Outline document.

Vrámci platných Pravidiel pro organizaci studia na Matematicko-fyzikální fakultě Univerzity Karlovy (ze dne 14.června, 2017), sa vzhľadom k Čl. 8, dds.2 týchto pravidiel týmto vyhlasuje, že povaha předmětu vylučuje právo studenta na jeden řádny a dva opravné termíny pro získaní zápočtu. Získaní zápočtu sa riadi výhradne pravidlami uvedenými vyššie a detailne popisanými v tomto NMSA 407 outline documente.