| 
        Lecturer(s)
     | 
    
        
            
                - 
                    Picek Jan, prof. RNDr. CSc.
                
 
            
                - 
                    Skalská Hana, prof. RNDr. CSc.
                
 
            
                - 
                    Linda Bohdan, doc. RNDr. CSc.
                
 
            
                - 
                    Kubanová Jana, doc. PaedDr. CSc.
                
 
            
         
     | 
    | 
        Course content
     | 
    
        Probability and statistics: Probability distrubution models and their application in inference, analysis of cathegorical data, parametric and non-parametric hypothesis testing, factorial experiments. Multivariate methods: regression models and inference in linear regression, discriminant function analysis or other types of predictive models (logistic regression, decision trees, etc.), cluster analysis. Decision support systems: modelling, causality, sample survey problems and generalization, data and their usage in decision making, software for data analysis, data visualization.  
         
         
     | 
    | 
        Learning activities and teaching methods
     | 
    
        
        Monological explanation (lecture, presentation,briefing)
        
            
                    
                
                    
                    - Class attendance
                        - 560 hours per semester
                    
 
                
             
        
        
     | 
    
    
        
        
            | 
                Learning outcomes
             | 
        
        
            
                
                Advanced methods of  inductive statistics. Students should develop skills and knowledge specific for statistical considerations supporting a comprehensive approach to solutions of real problems.
                 
                Students obtain knowledge in given course in accordance with requirements and course programme.
                 
                
             | 
        
        
            | 
                Prerequisites
             | 
        
        
            
                
                
                Knowledge in given course in accordance with requirements and course programme.
                
                
                    
                        
                    
                    
                
                
  
             | 
        
        
            | 
                Assessment methods and criteria
             | 
        
        
            
                
                    
                        Combined examination, Oral exam
                        
                        
                         
                        
                    
                    
                
                 Elaboration of a project as instructed by a teacher. The defense of the project is part of the exam.
                 
             | 
        
    
    | 
        Recommended literature
     | 
    
        
            
                
                - 
                    ANDERSON, T. W. An Introduction to Multivariate Statistical Analysis. 2003. ISBN 978-0-471-36091-9.
                
 
            
                
                - 
                    Dalgaard, P. Introductory Statistics with R. 2008. ISBN 978-0-387-79053-4.
                
 
            
                
                - 
                    Hebák, P. a kol. Vícerozměrné statistické metody. Informatorium, Praha, 2007. 
                
 
            
                
                - 
                    HEBÁK, P. et al. Vícerozměrné statistické metody (3). Informatorium.. Praha, 2005. ISBN 80-7333-039-3.
                
 
            
                
                - 
                    Hebák, P., Hustopecký, J., Malá, I. Vícerozměrné statistické metody (2). Informatorium, Praha, 2005. ISBN 80-7333-036-9.
                
 
            
                
                - 
                    Isson, J. a Harriot, J. Win with Advanced Business Analytics: Creating Business Value from Data. 
                
 
            
                
                - 
                    JUREČKOVÁ, J., P. K. SEN a J. PICEK. Methodological Tools in Robust and Nonparametric Statistics. 2013. ISBN 978-1-4398-4068-9.
                
 
            
                
                - 
                    KING, R.S. Cluster Analysis and Data Mining: An Introduction. 2015. ISBN 978-1938549-38-0.
                
 
            
                
                - 
                    Kubanová, J. Statistické metody pro ekonomickou a technickou praxi. 
                
 
            
                
                - 
                    Linda, B. Pravděpodobnost. 
                
 
            
                
                - 
                    REIMANN C., P. FILZMOSER, R. GARRETT a R. DUTTER. Statistical Data Analysis Explained. 2008. ISBN 978-0-470-98581-6.
                
 
            
                
                - 
                    ŘEZANKOVÁ, H. Analýza dat z dotazníkových šetření. 2. vyd. Praha: Professional Publishing, 2010. 
                
 
            
                
                - 
                    S. COLES. An Introduction to Statistical Modeling of Extreme Values. 2001. ISBN 978-1-85233-459-8.
                
 
            
                
                - 
                    Skalská, H., Stránský, P. Základy biostatistiky. Karolinum, Praha, 2007. 
                
 
            
                
                - 
                    Wonnacott, T.H., Wonnacott, R.J. Introductory Statistics for Business and Economics. New York : John Wiley & Sons, 1990. ISBN 0-471-61517-X.
                
 
            
                
                - 
                    Zhao, Z. R and Data Mining: Examples and Case Studies. 2013. ISBN 978-0-12-396963-7.
                
 
            
         
         
         
     |