Course code:  RRASA 
Course title in language of instruction:  Applied Statistics in English 
Course title in Czech:  Applied Statistics in English 
Course title in English:  Applied Statistics in English 
Mode of completion and number of credits:  Exam (6 credits) (1 ECTS credit = 28 hours of workload) 
Mode of delivery/Timetabled classes:  fulltime, 2/2 (hours of lectures per week / hours of seminars per week) 
Language of instruction:  English 
Level of course:  bachelor 
Semester:  SS 2018/2019 
Name of lecturer:  Ing. Pavel Hrabec (examiner, instructor, lecturer) doc. Ing. Kristina Somerlíková, Ph.D. (supervisor) 
Prerequisites:  none 

Aims of the course: 
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 contents: 
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 



Learning outcomes and competences: 
Generic competences:     Ability to solve problems    Ability to work independently    Basic computing skills    Science and research skills    Skilled at utilizing and processing information 
 Specific competences:     Ability of numeric and graphic presentation of mass data analysis    Ability to analyse mass sectional and dynamic data    Ability to interpret results and apply statistical knowledge    Ability to manage basic principles of quantitative and qualitative mass data collection and processing 


Type of course unit:  required 
Year of study:  Not applicable  the subject could be chosen at anytime during the course of the programme. 
Work placement:  There is no compulsory work placement in the course unit. 
Recommended study modules:   

Learning activities and study load (hours of study load): 
Type of teaching method  Daily attendance  Direct teaching  lecture  28 h  practice  28 h  Selfstudy  preparation for exam  42 h  preparation for regular assessment  14 h  preparation for regular testing  28 h  elaboration of reports  28 h  Total  168 h 


Assessment methods: 
Hand in 4 assignments to be solved individually and solution of 2 partial written tests, each of 60minute duration focused on practical examples and theory. The sum of scores from assignments and tests is credited for final grade with 50% pass rate. 

Recommended reading: 
Type  Author  Title  Published in  Publisher  Year  ISBN 

RQ   Statistics for engineers and scientists  Boston  McGrawHill   0071214925  RQ  GUJARATI, D N.  Basic econometrics  Boston  McGraw Hill  2003  0071123423  RQ  ADAMEC, V.  Applied statistics: statistics I : descriptive statistics : linear regression and correlation : categorical data : time series : statistical indices  Brno  Mendelova univerzita v Brně  2010  9788073754556 
