548-0093/03 – Quantitative methods in geography (KMG)

Gurantor departmentDepartment of GeoinformaticsCredits6
Subject guarantorprof. Ing. Igor Ivan, Ph.D.Subject version guarantorprof. Ing. Igor Ivan, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year2Semesterwinter
Study languageEnglish
Year of introduction2021/2022Year of cancellation
Intended for the facultiesHGFIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
IVA026 prof. Ing. Igor Ivan, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+3
Part-time Credit and Examination 8+12

Subject aims expressed by acquired skills and competences

- Student demonstrates knowledge: • basic concepts of statistics • basic methods Exploratory data analysis and spatial Exploratory data analysis • assessment of the spatial distribution of geographic data • correlation, autocorrelation and spatial autocorrelation • regression modeling - Students can: • apply introduced quantitative methods • analyze geographic data and take advantage of the spatial aspect of these data - Student is able to: • interpret the results • decide on appropriate procedures based on the analyzed data and the results of quantitative analysis

Teaching methods

Lectures
Tutorials

Summary

The main goal of this course is to introduce to students principles and methods of quantitative analysis in geography. It provides an overview of basic methods for statistical evaluation of data with the focus on the spatial aspects of geographic data. This course introduces both classical statistical methods of data analysis, as well as derived alternatives for quantitative analysis of geographic data.

Compulsory literature:

ROGERSON, P.A. (2019): Statistical Methods for Geography: A Student’s Guide, SAGE Publications Ltd, 432 P. ISBN 978-1526498809. SMITH, M. J., GOODCHILD, M. F., LONGLEY, P. A. (2006): Geospatial Analysis, Troubador Publishing Ltd., 414 p. Dostupné z: . FOTHERINGHAM, A.S., BRUNSDON, C., CHARLTON, M. (2000): Quantitative Geography: Perspectives on Spatial Data Analysis. Sage Publications Ltd., 272 p. O'SULLIVAN, D., UNWIN, D. (2010): Geographical Information Analysis. Wiley. 432 p.

Recommended literature:

SMITH, M.J.: Statistical Analysis Handbook [online]. Dostupné z: . FOTHERINGHAM, A. S., ROGERSON, P. A. (eds.) (2009): The SAGE Handbook of Spatial Analysis, Sage Publications Ltd., 528 p. McGREW, Jr., CHAPMAN, J., MONROE, C.B. (2009): An Introduction to Statistical Problem Solving in Geography, Waveland Pr Inc, 254 p. BURT, J.E., BARBER, G.M. (2009): Elementary Statistics for Geographers Hardcover, Guilford Press, 653 P.

Way of continuous check of knowledge in the course of semester

Students are asked about knowledge from areas that they should have already known from previous lectures. They also work on individual tasks. They must pass writing and oral exam.

E-learning

Other requirements

No other requirements are defined.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1) Definition, history and goals of quantitative methods in geography. Basic statistical terms. 2) Types of variables and their relationship to quantitative analysis in geography. Basics of graphical visualisations of geographical data. 3) Basic theoretical distributions 4) Data transformation and standardization. 5) Exploratory data analysis (graphical and numerical description of the data distribution). 6) Exploratory Spatial Data Analysis. Trend analysis. 7) Inferential Statistic - t-test, ANOVA 8) Spatial statistics for point pattern. Randomness and Randomization. Declustering. 9)Introduction to inferential statistical tests for point pattern. 10) Correlation analysis. 11) Spatial autocorrelation. 12) Regression analysis 13) Local regression analysis, GWR. 14) Introduction to analysis of time series

Conditions for subject completion

Part-time form (validity from: 2021/2022 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67 (67) 18 3
                Writing Exam Written examination 50  26
                Oral Exam Oral examination 17  8
Mandatory attendence participation: According to the teacher's specification.

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Conditions for subject completion and attendance at the exercises within ISP: Instead of attending lectures, it is necessary to study the materials that are given for the course. In order to receive credit, the student must complete four separate tasks (according to the lecturer's assignment).

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2024/2025 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2024/2025 (B0532A330042) Geoinformatics AGI P English Ostrava 2 Compulsory study plan
2023/2024 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2023/2024 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2023/2024 (B0532A330042) Geoinformatics AGI P English Ostrava 2 Compulsory study plan
2022/2023 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan
2022/2023 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2021/2022 (B0532A330034) Geoinformatics AGI K Czech Ostrava 2 Compulsory study plan
2021/2022 (B0532A330034) Geoinformatics AGI P Czech Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
ECTS - FMG 2024/2025 Full-time English Optional 501 - Study Office stu. block
ECTS - FMG 2023/2024 Full-time English Optional 501 - Study Office stu. block

Assessment of instruction



2022/2023 Winter