Statisctics 1

It is not possible to register for the course U63E3101 if the student is concurrently registered for or has previously completed the course 32BE-P-STA1-01 (mutually exclusive courses).

The requirement for course U63E3101 can be fulfilled by substitution with the course 32BE-P-STA1-01.

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Institute of Economic Studies

Synopsis:

Upon successful completion, students will acquire basic knowledge of applied statistics in the field of descriptive techniques of data sets, regression and correlation analysis, variance analysis, regression analysis, design and evaluation of experiments, hypothesis testing and time series analysis. After completing the course, students will be ready to use these methods in subsequent studies and practical tasks in a business environment.

Requirements:

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.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.

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:

No time-table has been prepared for this course

The course is a part of the following study plans: