Basics of Experimantal Data Processing

Code	Completion	Credits	Range
16ZEDB	ZK	2	2+0

Lecturer:

Kateřina Pilařová (guarantor)

Tutor:

Supervisor:

Synopsis:

Statistical analysis of experimental data; univariate data; calibration; regression; multivariate data.

Requirements:

Syllabus of lectures:

1. Introduction

2. Charakteristics of statistical distributions (univariate data)

3. Exploratory data analysis

4. Testing of hypothesis

5. Analysis of variance (ANOVA)

6. Correlation analysis

7. Linear regression analysis

8. Principal of nonlinear regression analysis

9. Calibration

10. Interpolation and approximation

11. Basic of statistical analysis of multivariate data - enters data

12. Statistical analysis of multivariate data - test of characteristics

13. Multivariate statistical analysis - methods of latent variables

14. Multivariate statistical analysis - classification methods

Syllabus of tutorials:

Study Objective:

Knowledge:

Orientation in application of statistical methods in experimental data processing.

Abilities:

Independent treatment of experimental data.

Study materials:

Key references:

[1] M.Meloun, J.Militky, Statistical analysis of experimental data, ACADEMIA Prague 2004 (in Czech)

Recommended references:

[2] M.Meloun, J.Militky, M.Hill, Computer analysis of multivariant data in examples, ACADEMIA Prague 2005 (in Czech)

Note:

Time-table for winter semester 2022/2023:

Time-table is not available yet

Time-table for summer semester 2022/2023:

Time-table is not available yet

The course is a part of the following study plans: