| Course title | Spatial Data Analysis |
|---|---|
| Course code | KMA/APD |
| Organizational form of instruction | Lecture + Exercise |
| Level of course | Master |
| Year of study | not specified |
| Semester | Winter |
| Number of ECTS credits | 5 |
| Language of instruction | Czech |
| Status of course | Compulsory, Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
|---|
|
| Course content |
|
- Types of spatial dependent data and its preprocessing with a statistical software - Visualization of spatial data - Spatial correlation - Spatial point patterns - Areal data - Basics of spatio-temporal data analysis - Additional topics related to spatial dependency
|
| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
|
The aim is to acquaint students with the basic procedures in the analysis of spatial dependent data.
The student will be able to independently analyze spatial dependent data, to visualize and interpret the results. |
| Prerequisites |
|
Basics of probability theory, statistics, and work with a statistical software.
|
| Assessment methods and criteria |
|
unspecified
Seminar work and an oral exam. Active participation. |
| Recommended literature |
|
| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| Faculty: Faculty of Science | Study plan (Version): Mathematics (2023) | Category: Mathematics courses | 2 | Recommended year of study:2, Recommended semester: Winter |
| Faculty: Faculty of Science | Study plan (Version): Applied Mathematics (2023) | Category: Mathematics courses | 2 | Recommended year of study:2, Recommended semester: Winter |