Course title:  Applied Statistics 
Semester:  WS 2018/2019 
Course supervisor:  doc. Ing. Kristina Somerlíková, Ph.D. 
Supervising department:  Department of Regional and Business Economics (FRDIS) 
Time allowance:  fulltime, 2/2 (hours of lectures per week / hours of seminars per week) parttime, 20/0 (lectures per period / seminars per period) 
Prerequisites for registration:  not Applied Statistics in English 
Type of study:  consulting 
Form of teaching:  lecture, seminar 
Mode of completion and credits:  Exam (6 credits) 

Course objective: 
Acquirement of theoretical knowledge and basic calculation procedures in the field of descriptive statistics, assessment of relationships between numerical and categorical variables, description of time series and statistical comparisons as applied to social and economic processes. Skills to use statistical tools and functions of Microsoft Excell package. 

Course content: 
1.  Introduction into statistics (allowance 2/4)   a.  The term of statistics, methods, terminology, stages of statistical investigation  b.  Statistical means of expressing results, tables and diagrams  c.  Univariate statistical series, distribution of frequencies, variable classification  d.  Important values: extremes, mode, quantiles  e.  Analysis of structure, Lorenz curve and Gini index 
 2.  Descriptive statistics (allowance 4/10)   a.  Measuring the location and variability  b.  Moments and system of moment characteristics  c.  Basic types of statistical dependencies, terminology  d.  Regression and the least squares method, correlation index, determination  e.  Simple linear correlation, joint regression lines and correlation coefficient  f.  Classification of categorical data, analysis of contingency tables 
 3.  Statistical dynamics (allowance 6/14)   a.  Time series, definition, types, derived time series  b.  Elementary characteristics of dynamic events; moving averages  c.  Description of trend; trivial model of seasonality; assessment of model quality  d.  Measurements and comparisons of magnitude of particular events, types of quantities for comparisons, definitions and types of relative numbers  e.  Indices in wide and narrow sense, concept, types. Individual complex indices  f.  Aggregate indices, value index and related indices, decomposition of indices and corresponding absolute differences 



Teaching methods and workload (hours of workload): 
Type of teaching method  Daily attendance  Combined form  Direct teaching  lecture  28 h  20 h  practice  28 h  0 h  Selfstudy  preparation for exam  60 h  48 h  preparation for regular assessment  12 h  40 h  preparation for regular testing  40 h  0 h  elaboration of reports  0 h  60 h  Total  168 h  168 h 


Key words: 
none 

Course completion: 
Solution of 6 practical examples to be solved individually and 2 partial tests (collectively, they may grant some extra points to final exam results) within semester. 60minute written exam, 50 % theory, 50 % examples, with 50% pass rate each. 

Course methods:  12 hours of lectures and 28 hours of computer lab sessions, practicing mainly analyses in MS Excel environment. In total, 40 hours of instruction. 

Reading list: 
Basic:  HINDLS, R. et al. Statistika pro ekonomy. 8th ed. Praha: Professional Publishing, 2007. 415 p. ISBN 9788086946436.  MINAŘÍK, B. Statistika I: popisná statistika. 3rd ed. Brno: Mendelova zemědělská a lesnická univerzita v Brně, 2008. ISBN 9788073751524.  MAREK, L. et al. Statistika pro ekonomy: aplikace. 2nd ed. Praha: Professional Publishing, 2007. 485 p. ISBN 9788086946405. 
  Recommended:  Minařík, B. Statistika. Elearningová studijní opora ve formátu PDF (dostupná v UIS). 


Study plans: 
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Run in the period of:  WS 2019/2020, SS 2018/2019, SS 2017/2018, WS 2017/2018, SS 2016/2017, WS 2016/2017 (and older) 
Course tutor:  doc. Ing. Kristina Somerlíková, Ph.D. (examiner, instructor, lecturer, supervisor) 
Teaching language:  Czech 
Town:   item not defined  