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        Lecturer(s)
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                    Urbánek Tomáš, Ing. Ph.D.
                
 
            
         
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        Course content
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        <h5><b><u>First Part of the Semester</u></b></h5> <ul>     <li>Basic Concepts</li>     <li>Data and Descriptive Statistics of Central Tendency         <ul>             <li>Types of data</li>             <li>Mean</li>             <li>Median</li>         </ul>     </li>     <li>Descriptive Statistics of Variance and Shape         <ul>             <li>Variance</li>             <li>Skewness</li>             <li>Kurtosis</li>         </ul>     </li>     <li>Probability         <ul>             <li>Axioms of probability</li>             <li>Definition of probability</li>         </ul>     </li>     <li>Conditional Probability and Bayes' Theorem         <ul>             <li>Total probability</li>             <li>Conditional probability</li>             <li>Bayes' theorem</li>         </ul>     </li> </ul>  <h5><b><u>Second Part of the Semester</u></b></h5> <ul>     <li>Random Variable 1         <ul>             <li>Probability function</li>             <li>Probability density function</li>             <li>Cumulative distribution function</li>         </ul>     </li>     <li>Random Variable 2         <ul>             <li>Quantile function</li>             <li>Reliability function</li>             <li>Hazard function</li>         </ul>     </li>     <li>Distribution of Discrete Random Variable         <ul>             <li>Uniform distribution</li>             <li>Geometric distribution</li>             <li>Hypergeometric distribution</li>             <li>Binomial distribution</li>             <li>Poisson distribution</li>         </ul>     </li>     <li>Distribution of Continuous Random Variable 1         <ul>             <li>Uniform continuous distribution</li>             <li>Normal distribution</li>             <li>Exponential distribution</li>             <li>Weibull distribution</li>         </ul>     </li>     <li>Distribution of Continuous Random Variable 2         <ul>             <li>Student's distribution</li>             <li>Chi-square distribution</li>             <li>F-distribution</li>         </ul>     </li> </ul> 
         
         
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        Learning activities and teaching methods
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        Lecturing
        
            
                    
                
                    
                    - Participation in classes
                        - 52 hours per semester
                    
 
                
                    
                    - Preparation for examination
                        - 40 hours per semester
                    
 
                
                    
                    - Preparation for course credit
                        - 20 hours per semester
                    
 
                
                    
                    - Home preparation for classes
                        - 13 hours per semester
                    
 
                
             
        
        
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        | prerequisite | 
|---|
| Knowledge | 
|---|
| Knowledge of basic higher mathematics (the investigation of functions, derivatives and integrals).   | 
| Knowledge of basic higher mathematics (the investigation of functions, derivatives and integrals).   | 
| Knowledge of basic higher mathematics (the investigation of functions, derivatives and integrals).  | 
| Knowledge of basic higher mathematics (the investigation of functions, derivatives and integrals).  | 
| learning outcomes | 
|---|
| Defines concepts associated with data and descriptive statistics of location | 
| Defines concepts associated with data and descriptive statistics of location | 
| Describes statistics such as variance, skewness, and kurtosis, which characterize dispersion and the shape of distributions | 
| Describes statistics such as variance, skewness, and kurtosis, which characterize dispersion and the shape of distributions | 
| Explains fundamental probability concepts | 
| Explains fundamental probability concepts | 
| Explains concepts associated with random variables | 
| Explains concepts associated with random variables | 
| Lists and defines various distributions of discrete random variables | 
| Lists and defines various distributions of discrete random variables | 
| Lists and defines various distributions of continuous random variables | 
| Lists and defines various distributions of continuous random variables | 
|  Defines probability | 
|  Defines probability | 
| Explains the concept of random variable | 
| Explains the concept of random variable | 
| Skills | 
|---|
| Addresses practical tasks that involve the application of probability and descriptive statistics | 
| Addresses practical tasks that involve the application of probability and descriptive statistics | 
| Uses probability functions for different types of random variables | 
| Uses probability functions for different types of random variables | 
| Applies distribution functions for random variables based on provided information | 
| Applies distribution functions for random variables based on provided information | 
| Conducts the analysis of random variables | 
| Conducts the analysis of random variables | 
| Resolves issues related to diverse distributions of random variables and interprets their meaning | 
| Resolves issues related to diverse distributions of random variables and interprets their meaning | 
| Calculates the basic location characteristics of the data | 
| Calculates the basic location characteristics of the data | 
| Calculates the basic variability characteristics of the data | 
| Calculates the basic variability characteristics of the data | 
| teaching methods | 
|---|
| Knowledge | 
|---|
| Lecturing | 
| Lecturing | 
| assessment methods | 
|---|
| Grade (Using a grade system) | 
| Grade (Using a grade system) | 
    
    
    | 
        Recommended literature
     | 
    
        
            
                
                - 
                    Clarke, G. M., Cooke, D. A basic course in statistics. 2nd ed. London: Edward Arnold,, 1983. ISBN 0-7131-3496-8.
                
 
            
                
                - 
                    FELLER. An Introduction to Probability Theory and Its Applications, Volume II.. New York: Wiley, 1971. 
                
 
            
                
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                    FREUND, J. E., WALPOLE, R. E. Mathematical Statistics.. Englewood Cliffs: Prantice-Hall, 1987. ISBN 0135621178.
                
 
            
                
                - 
                    Hogg, R.V., Craig, A.T. Introduction to mathematical statistics. 4th ed. New York: Macmillan Publishing Company, 1989. 
                
 
            
                
                - 
                    JAMES, G., WITTEN, D., HASTIE, T., TIBSHIRANI, R. An introduction to statistical learning: with applications in R. New York: Springer, 2013. ISBN 978-1-4614-7137-0.
                
 
            
                
                - 
                    Kropáč, Jiří. Základy teorie pravděpodobnosti a matematické statistiky. Zlín : UTB, 2003. ISBN 80-7318-139-8.
                
 
            
                
                - 
                    KUHN, M., JOHNSON, K. Applied predictive modeling. New York: Springer, 2013. ISBN 978-1-4614-6848-6.
                
 
            
                
                - 
                    Likeš, Jiří, Machek, Josef. Matematická statistika - Matematika pro vysoké školy technické, sešit XI. Praha : SNTL, 1983. 
                
 
            
                
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                    Lloyd, E. H. Handbook of applicable mathematics 2 : probability. Chicester Wiley, 1980. ISBN 0-471-27821-1.
                
 
            
                
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                    MONTGOMERY, D. C. Introduction to Statistical Quality Control. vyd. 6.. John Wiley & Sons, Inc,, 2009. ISBN 978-0470169926.
                
 
            
                
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                    PECK, R., OLSEN, CH., DEVORE, J., L. Introduction to Statistics and Data Analysis, Enhanced Review Edition (4th Edition). Duxbury Press, 2011. ISBN 0840054904.
                
 
            
                
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                    PESTMAN, W. R. Mathematical Statistics: An Introduction. New York: Walter de Gruyter, 1998. 
                
 
            
                
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                    ROSS, S. M. Introductory Statistics. 3rd ed.. Academic Press,, 2010. ISBN 0123743885.
                
 
            
                
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                    Swoboda, Helmut. Moderní statistika. Vyd. 1. Praha : Svoboda, 1977. 
                
 
            
         
         
         
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