Course syllabus RRASA - Applied Statistics in English (FRDIS - SS 2017/2018)

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Course code:
Course title in Czech: Applied Statistics in English
Course title in English: Applied Statistics in English
SS 2017/2018
Mode of completion and number of credits:
Exam (6 credits)
Mode of delivery and timetabled classes: full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Level of course:
Course type:
Type of delivery:
usual, consulting
Mode of delivery for our mobility students abroad:
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Language of instruction:
Course supervisor: doc. Ing. Kristina Somerlíková, Ph.D.
Course supervising department:
Faculty of Regional Development and International Studies
Ing. Pavel Hrabec (examiner, instructor, lecturer)
doc. Ing. Kristina Somerlíková, Ph.D. (supervisor)
Timetable in this semester:
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Aim of the course and learning outcomes:
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
Statistical means of expressing results, tables and diagrams
c.Univariate statistical series, distribution of frequencies, variable classification
Important values: extremes, mode, quantiles
Analysis of structure, Lorenz curve and Gini index

Descriptive statistics (allowance 4/10)
Measuring the location and variability
Moments and system of moment characteristics
Basic types of statistical dependencies, terminology
Regression and the least squares method, correlation index, determination
Simple linear correlation, joint regression lines and correlation coefficient
Classification of categorical data, analysis of contingency tables

Statistical dynamics (allowance 6/14)
Time series, definition, types, derived time series
Elementary characteristics of dynamic events; moving averages
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
Aggregate indices, value index and related indices, decomposition of indices and corresponding absolute differences

Learning activities and teaching methods:
Type of teaching methodDaily attendance
28 h
practice28 h
preparation for exam
42 h
preparation for regular assessment
14 h
preparation for regular testing
28 h
elaboration of reports
28 h
168 h
Assessment methods:
Hand in 4 assignments to be solved individually and solution of 2 partial written tests, each of 60-minute duration focused on practical examples and theory. The sum of scores from assignments and tests is credited for final grade with 50% pass rate.
Assessment criteria ratio:
Requirement type
Daily attendance
0 %
Recomended reading and other learning resources:
Statistics for engineers and scientists. Boston: McGraw-Hill, 869 p. ISBN 0-07-121492-5.
GUJARATI, D N. Basic econometrics. 4th ed. Boston: McGraw Hill, 2003. 1002 p. ISBN 0-07-112342-3.
ADAMEC, V. Applied statistics: statistics I : descriptive statistics : linear regression and correlation : categorical data : time series : statistical indices. 1st ed. Brno: Mendelova univerzita v Brně, 2010. 119 p. ISBN 978-80-7375-455-6.

Course listed in study plans for this semester:
Programme B-INTSE International Territorial Studies, full-time form, initial period WS 2016/2017
Programme B-REDA Regional Development, full-time form, initial period WS 2016/2017
Field of study B-ITSE-IDSE International Development Studies, full-time form, initial period WS 2016/2017
Field of study B-RDE-SEDRE Socioeconomic and Environmental Development of Regions, full-time form, initial period WS 2016/2017
Course listed in previous semesters: SS 2019/2020, WS 2019/2020, SS 2018/2019, WS 2018/2019, WS 2017/2018, SS 2016/2017 (and older)
Teaching place:
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Last modification made by Bc. Vít Karber on 12/01/2017.

Type of output: