      # Course syllabus ST1A - Statistics (FBE - WS 2019/2020)

ECTS syllabus          Syllabus          Timetable

Czech          English

Course code: ST1A
Course title in language of instruction: Statistics
Course title in Czech: Statistics
Course title in English: Statistics
Mode of completion and number of credits: Exam (6 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes: full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Language of instruction: English
Level of course: bachelor
Semester: WS 2019/2020
Name of lecturer: doc. Ing. Václav Adamec, Ph.D. (supervisor)
RNDr. Karel Mikulášek, Ph.D. (examiner, instructor, lecturer)
Prerequisites: Mathematics I

Aims of the course:
The course objective is acquirement of theoretical knowledge and basic calculation procedures in the field of descriptive statistics, probability theory, estimation and inferential statistics (confidence intervals, hypothesis tests, non-parametrics). The course is expected to prepare students for use of statistics in economic or managerial reality and elaboration of final diploma projects (theses).

Course contents:
1.Introduction to statistics (allowance 8/8)

 a. The term of statistics, methods, terminology, tables and plots, stages of statistical investigation, frequency tables b. Statistical data, characteristics of level, variability, skewness and kurtosis

2.Probability calculations (allowance 6/8)

 a. Elementary terminology of the probability and distribution theory, definitions b. Repeated trials, with and without replacement c. Random variables, probability distribution, distribution function, probability density function, probability mass function d. Property of random variables e. Important distributions of continuous and discrete random variables

3.Fundamentals of inferential statistics (allowance 12/10)

 a. Probability distributions of some important test statistics b. Population and random sample c. Point estimation, construction and properties d. Confidence intervals, construction and properties e. Statistical hypothesis tests, steps, errors f. Parametric and nonparametric tests

Learning outcomes and competences:
Generic competences:

 - Ability to analyse and synthesize - Ability to apply knowledge - Basic computing skills - Communication in second language - Skilled at utilizing and processing information

Specific competences:

 - Students are able to test statistical hypotheses and apply the results in practice. - Students are able to work with probabilities and utilize probability and distribution theory in statistical testing. - Students can calculate statistical characteristics, interpret results with applications to data - Students understand diagrams and are able to utilize plots to interpret the data

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: -

 Type of teaching method Daily attendance Direct teaching lecture 26 h practice 26 h Self-study preparation for exam 30 h preparation for regular assessment 31 h preparation for regular testing 20 h writing of seminar paper 35 h Total 168 h

Assessment methods:
A student is eligible for the final exam in Statistics, if the following requirements were met: Attending 13 workshop lessons; a reasonable excuse may be accepted for not attending up to two workshops; passing a midterm test by receiving at least 50% of the maximum thirty points; taking active part in the workshops, which includes working on home assignments and presenting the results at the workshops. The final exam is worth 100 points. The minimum score required for a student to pass the exam is 50. The student grade shall be determined from the following table: 50 – 59 E, 60 – 69 D, 70 – 79 C, 80 – 89 B, 90 – 100 A.