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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Statistics 1

The course is not on the list Without time-table
Code Completion Credits Range Language
U63C3101 Z,ZK 6 2P+2C Czech
Vztahy:
It is not possible to register for the course U63C3101 if the student is concurrently registered for or has previously completed the course 32BC-P-STA1-01 (mutually exclusive courses).
The requirement for course U63C3101 can be fulfilled by substitution with the course 32BC-P-STA1-01.
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Institute of Economic Studies
Synopsis:

The study results are verified by the following forms of attestation:

a) Credit

b) Exam

The credit is awarded on completion of the requirements set by the teacher at the beginning of the semester. In the course of Statistics I, there is a minimum active participation in the 75% exercise, the preparation of the semester project in the required quality and scale, and passing the final test at the minimum level of 60%.

A subsequent examination is a form of attestation that examines knowledge of student principles and practices within the topics listed below for the Statistics I subject. The exam is always written and usually supplemented by the oral part.

Requirements:

The study results are verified by the following forms of attestation:

a) Credit

b) Exam

The credit is awarded on completion of the requirements set by the teacher at the beginning of the semester. In the course of Statistics I, there is a minimum active participation in the 75% exercise, the preparation of the semester project in the required quality and scale, and passing the final test at the minimum level of 60%.

A subsequent examination is a form of attestation that examines knowledge of student principles and practices within the topics listed below for the Statistics I subject. The exam is always written and usually supplemented by the oral part.

Syllabus of lectures:

1.Introduction to statistical issues, random variable, probability function, probability density, distribution function.

2.Basic types of distribution (discrete and continuous random variables), derivation of their essential numerical characteristics.

3.Numerical characteristics of random variables. Mathematical expectation of random variable, data types, mean value, variance, slope coefficient, spikes, quantal, median, modus.

4.Statistical file with one argument, regression and correlation analysis, derivation of coefficients of the equation of the line, assumptions of the linear regression model.

5.Nonlinear regression and correlation analysis, correlation field with the general course, addition function, determinant coefficient.

6.Application utilization of regression analysis for design of experiments, factor-response, factor-to-factor interactions, „single factor change“ problems, factorial design, variance analysis.

7.Statistical experimentation for two-level factors, factorial proposals 2n.

8.Binary synthesis of response quantity, removal of redundant experiment factors.

9.Statistical induction and its use in the management, statistical hypothesis, statistical tests, interval estimation, significance level, critical values, test criterion, type 1 and 2 error.

10.Statistical hypotheses Tests (parametric), difference test of (F-test, T-test).

11.The randomness test of the difference between empirical and theoretical frequencies (test א 2).

12.Statistical regulation. Shewhart's control diagrams.

13. Methods of multivariate analysis, external analysis, and internal analysis (principal component analysis, factor analysis, cluster analysis).

14. Choice of statistical method, classification of statistical methods, problems of significance tests, Bayesian approach, computationally intensive methods.

Syllabus of tutorials:

1. random variable, probability function, probability density, distribution function.

2.types of distribution (discrete and continuous random variables),

3.numerical characteristics of random variables.

4.statistical file with one argument, regression and correlation analysis

5.nonlinear regression and correlation analysis

6.application utilization of regression analysis for design of experiments, factor-response, factor-to-factor interactions

7.statistical experimentation for two-level factors, factorial proposals 2n.

8.binary synthesis of response quantity, removal of redundant experiment factors.

9.statistical hypotheses Tests (parametric),

10.randomness test of the difference between empirical and theoretical

frequencies

11. statistical interval of reliability

12.statistical regulation. - Shewhart's control diagrams.

13. Methods of multivariate analysis, external analysis, and internal analysis (principal component analysis, factor analysis, cluster analysis).

14. Choice of statistical method, classification of statistical methods, problems of significance tests, Bayesian approach, computationally intensive methods.

Study Objective:

After completing the course, students will be prepared to practically apply these methods in related subjects and practical problems in the corporate environment.

Study materials:

OBLIGATORY

Freedman D. (2007). Statistics, Third Edition. Norton & Company, Incorporated, W. W.ISBN-13: 978-0393970838

RECOMMENDED

Kutner, M., Nachtsheim, C., Neter, J., and Li, W. (2004). Applied Linear Statistical Models, McGraw-Hill/Irwin, Homewood, IL.

LIND, D., MARCHAL, W., WATHEN, S. (2015) Statistical Techniques in Business and Economics, (16th Edition). McGraw-Hill Education. ISBN-13: 978-0078020520.

TRIOLA, M., F. Essentials of Statistics (5th Edition). Pearson Education 2015. ISBN-13: 978-0321924599.

Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.) (p.178). Cheshire, CT: Graphics Press.

Note:
Further information:
https://moodle-vyuka.cvut.cz/course/view.php?id=5904
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-07-21
Aktualizace výše uvedených informací naleznete na adrese https://bilakniha.cvut.cz/en/predmet4989506.html