Statistics 1
Code  Completion  Credits  Range  Language 

32BCPSTA101  Z,ZK  6  2P+2C  Czech 
 Relations:
 It is not possible to register for the course 32BCPSTA101 if the student is concurrently registered for or has already completed the course U63C3101 (mutually exclusive courses).
 During a review of study plans, the course U63C3101 can be substituted for the course 32BCPSTA101.
 Course guarantor:
 Tomáš Macák
 Lecturer:
 Tomáš Löster, Tomáš Macák, Jiří Zmatlík
 Tutor:
 Tomáš Löster, Tomáš Macák, Jiří Zmatlík
 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, factorresponse, factortofactor interactions, „single factor change“ problems, factorial design, variance analysis.
7.Statistical experimentation for twolevel 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 (Ftest, Ttest).
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, factorresponse, factortofactor interactions
7.statistical experimentation for twolevel 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.
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 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.ISBN13: 9780393970838
RECOMMENDED
Kutner, M., Nachtsheim, C., Neter, J., and Li, W. (2004). Applied Linear Statistical Models, McGrawHill/Irwin, Homewood, IL.
LIND, D., MARCHAL, W., WATHEN, S. (2015) Statistical Techniques in Business and Economics, (16th Edition). McGrawHill Education. ISBN13: 9780078020520.
TRIOLA, M., F. Essentials of Statistics (5th Edition). Pearson Education 2015. ISBN13: 9780321924599.
Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.) (p.178). Cheshire, CT: Graphics Press.
 Note:
 Timetable for winter semester 2024/2025:
 Timetable is not available yet
 Timetable for summer semester 2024/2025:
 Timetable is not available yet
 The course is a part of the following study plans:

 BEMP prezenční studium od 22/23 (compulsory course)