Applied Statistics

Course guarantor:

Lecturer:

Pavla Pecherková, Evženie Uglickich

Tutor:

Pavla Pecherková, Evženie Uglickich

Supervisor:

Department of Applied Mathematics

Synopsis:

Descriptive statistics, data preprocessing, discretize continuous data. Hypothesis testing - continuous and discrete variables. Regression and correlation analysis. Multivariable methods - multiple regression analysis, logistic regression analysis, ROC curve, MANOVA, PCA, Factor analysis. Power analysis, preparation, processing and evaluation of hte experiment.

Requirements:

Completion of the course 11STAT (or alternatives)

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

To teach students the statistical processing of data, the choice of the correct processing procedure and the following evaluation of the obtained data, including adequate graphical outputs and the defense of the chosen procedure.

Study materials:

D.G. Kleinbaum, L.L.Kuper, A. Nizam, K.E. Muller: Applied Regression Analysis and Other Multivariable Methods 4th edition, ISBN-13: 978-049538496

Note:

Time-table for winter semester 2025/2026:

Time-table is not available yet

Time-table for summer semester 2025/2026:

Time-table is not available yet

The course is a part of the following study plans:

• Master Full-Time PL from 2022/23 (compulsory course)
• Master Part-Time PL from 2022/23 (compulsory course)
• Master Full-Time PL from 2023/24 (compulsory course)
• Master Part-Time PL from 2023/24 (compulsory course)
• Master Full-Time PL from 2024/25 (compulsory course)
• Master Part-Time PL from 2024/25 (compulsory course)