Home (CZ) | Teaching (CZ) | NMST552 |
Rko (CZ) |
| Lectures: | Tuesday 11:30 in K1 | |
| Tuesday 13:10 in K1 | ||
| Exercise class (SN): | Tuesday 17:20 in K4 | (Mgr. Stanislav Nagy, Ph.D.) |
| Exercise class (MM1): | Thursday 15:40 in K4 | (RNDr. Matúš Maciak, Ph.D.) |
| Exercise class (MM2): | Thursday 17:20 in K11 | (RNDr. Matúš Maciak, Ph.D.) |
If allowed by PANdemIC measures, the lecture proceeds in a lecture room by combination of slides projection and blackboard writing. More information will be provided during the first lecture. The slides and the course notes ("skripta") for the whole semester are available below. Nevertheless, do not print (if you want to print it) too many pages in advance. Both slides and notes are subject to (smaller) changes and/or corrections during the semester without further notice.
| Notes (PDF) | last update 02/09/2021 |
| Slides (PDF) | last update 02/09/2021 |
Recordings contain plus/minus the same information as in-person lectures and can be used as either supplement or occasional replacement of in-person lectures.
MP4 can be downloaded and played offline, nevertheless, each file will be removed from here at some point (not earlier than at the beginning of the week following the week for which the respective piece is intended). Stream is provided by stream.cuni.cz and will require SIS login, the link remains working till at least the end of semester.
| WEEK 1 (04/10 – 10/10) | |||
| Handnotes 1: PDF | Video 1 (75 min): | Stream | |
| Handnotes 2/1: PDF | Video 2/1 (61 min): | Stream | |
| WEEK 2 (11/10 – 18/10) | |||
| Handnotes 2/2: PDF | Video 2/2 (68 min): | Stream | |
| Handnotes 2/3: PDF | Video 2/3 (40 min): | Stream | |
| Handnotes 3: PDF | Video 3 (60 min): | Stream | |
| WEEK 3 (19/10 – 24/10) | |||
| Handnotes 4/1: PDF | Video 4/1 (43 min): | Stream | |
| Handnotes 4/2: PDF | Video 4/2 (112 min): | Stream | |
| Handnotes 4/3: PDF | Video 4/3 (105 min): | Stream | |
| WEEK 4 (25/10 – 31/10) | |||
| Handnotes 5/1: PDF | Video 5/1 (36 min): | Stream | |
| Handnotes 5/2: PDF | Video 5/2 (68 min): | Stream | |
| WEEK 5 (01/11 – 07/11) | |||
| Handnotes 5/4: PDF | Video 5/4 (105 min): | Stream | |
| Handnotes 6/1: PDF | Video 6/1 (88 min): | Stream | |
| Handnotes 6/2: PDF | Video 6/2 (49 min): | Stream | |
| WEEK 6 (08/11 – 14/11) | |||
| Handnotes 7: PDF | Video 7 (71 min): | Stream | |
| Handnotes 5/3: PDF | Video 5/3 (58 min): | Stream | |
| WEEK 7 (15/11 – 21/11) | |||
| Handnotes 8/1: PDF | Video 8/1 (70 min): | Stream | |
| Handnotes 8/2: PDF | Video 8/2 (65 min): | Stream | |
| Handnotes 5/5: PDF | Video 5/5 (115 min): | Stream | |
| WEEK 8 (22/11 – 28/11) | |||
| Handnotes 9/1: PDF | Video 9/1 (35 min): | Stream | |
| Handnotes 9/2: PDF | Video 9/2 (93 min): | Stream | |
| Handnotes 9/3: PDF | Video 9/3 (87 min): | Stream | |
| WEEK 9 (29/11 – 05/12) | |||
| Handnotes 9/4: PDF | Video 9/4 (26 min): | Stream | |
| Handnotes 10/1: PDF | Video 10/1 (99 min): | Stream | |
| Handnotes 10/2: PDF | Video 10/2 (110 min): | Stream | |
| WEEK 10 (06/12 – 12/12) | |||
| Handnotes 11/1: PDF | Video 11/1 (95 min): | Stream | MP4 |
| Handnotes 11/2: PDF | Video 11/2 (62 min): | Stream | MP4 |
| Handnotes 12/1: PDF | Video 12 (54 min): | Stream | MP4 |
| Handnotes 12/2: PDF | |||
| Supplement to 12: | R script | Data (RData) | Data description (PDF) |
| Video, part 1 (69 min): | Stream | MP4 | |
| Video, part 2 (73 min): | Stream | MP4 | |
| WEEK 11 (13/12 – 19/12) | |||
| Handnotes 14/1: PDF | Video 14/1 (67 min): | Stream | MP4 |
| Handnotes 14/2: PDF | Video 14/2 (66 min): | Stream | MP4 |
| Handnotes 14/3: PDF | Video 14/3 (53 min): | Stream | MP4 |
| WEEK 12 (20/12 – 26/12) | |||
| Handnotes 16/1: PDF | Video 16/1 (75 min): | Stream | MP4 |
| Handnotes 16/2: PDF | Video 16/2 (42 min): | Stream | MP4 |
| Handnotes 16/3: PDF | Video 16/3 (89 min): | Stream | MP4 |
| WEEK 13 (03/01 – 09/01) | |||
| Piece 13/1 contains mostly repetition of materials covered by previous lectures | |||
| as well as those covered by the Mathematical Statistics 1 course. | |||
| Handnotes 13/1: PDF | Video 13/1 (40 min): | Stream | MP4 |
| Handnotes 13/2: PDF | Video 13/2 (92 min): | Stream | MP4 |
This course closely follows the bachelor study branch General Mathematics and especially its subbranch Stochastics. The course hence builds upon decent knowledge of a classical mathematical thinking (theorem, proof, ...), knowledge acquired during very basic courses (mathematical analysis, linear algebra, ...) and also on intermediate knowledge of probability theory and mathematical statistics. The most important areas of general mathematics and mathematical statistics which are unavoidable to be able to follow this course include:
This course is not a cook-book course on linear regression and it does not make much sense to follow it without having a knowledge described above.
All information related to the exercise classes is (will be) available at the central exercise classes webpage.
Exercise classes are synchronized. Content of the classes held in the same week is approximately the same.
The course is supplemented by the R package mffSM which contains example datasets used throughout the course and few additional small functions related to processing of the linear model fit. Upon download (from the link below, not from CRAN), the package can be installed in R in a standard way (``from a local repository''). Windows binary file is intended for the MS Windows users (as the title suggests), the source code is intended for users of other (mostly more reliable) operating systems where it is a standard to compile the package from its source (Linux, Mac etc.). The mffSM package no more depends on packages colorspace, lattice, car, which are available in a standard way from CRAN. All those dependency packages should normally be automatically installed if the installation of the mffSM package is performed directly from the R console on an Internet-connected computer using the command (its appropriately modified analogy):
install.packages("PATH_WHERE_DOWNLOADED/mffSM_1.2.[tar.gz,zip]", repos = NULL)| Source code: | mffSM_1.2.tar.gz |
| Windows binary: | mffSM_1.2.zip |
R tutorials show the R analyses that are based on theory given during the lectures. They also provide the code used to prepare majority of the output/plots that is used during the lectures as illustrations. The R tutorials may serve as a reference for the assignments performed during the exercise classes or required in homeworks.
The R scripts provided below assume that the content of the .Rprofile is sourced at start.