SubjectsSubjects(version: 947)
Course, academic year 2023/2024
  
Statistics 1 - B501009
Title: Statistika 1
Guaranteed by: Department of Economics and Management (837)
Faculty: Central University Departments of UCT Prague
Actual: from 2023
Semester: both
Points: 6
E-Credits: 6
Examination process:
Hours per week, examination: 2/2, C+Ex [HT]
Capacity: winter:55 / 55 (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
For type: Bachelor's
Note: course can be enrolled in outside the study plan
enabled for web enrollment
you can enroll for the course in winter and in summer semester
Guarantor: Koťátková Stránská Pavla Ing. Ph.D.
Interchangeability : AB501009
This subject contains the following additional online materials
Annotation -
Last update: Koťátková Stránská Pavla Ing. Ph.D. (13.09.2023)
In Statistics I, students are introduced to the basics of probability theory and statistics and practice theoretical concepts on a variety of practical problems. Students will also learn the basics of processing, presentation and interpretation of data. The course is a preparation for further exploration of statistical methods for elementary economic analysis. and social phenomena. Students will learn to distinguish situations and appropriate methods for given circumstances and types of data. Will instruction in the proper presentation and interpretation of data and results will also be provided. Selected topics will be presented in the MS Excel and Gretl computing environments.
Literature - Czech
Last update: Krajčová Jana Mgr. Ph.D., M.A. (15.09.2020)

Z: BUDÍKOVÁ, M., KRÁLOVÁ, M., MAROŠ, B. (2010), Průvodce statistickými metodami. Praha: Grada Publishing. ISBN 978-80-247-3243-5.

D: ANDĚL, J. (2002), Základy matematické statistiky, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Preprint.

D: HENDL, J. (2004), Přehled statistických metod zpracování dat, Praha, Portál. ISBN 80-7178-820-1

D: KOŽÍŠEK, J., STIEBEROVÁ, B.: Statistika v příkladech, Verlag Dashofer, Praha 2012.

D: HINDLS, R., HRONOVÁ, S. a kol. (2007), Statistika pro ekonomy, Professional publishing. ISBN 978-80-86946-43-6.

D: LIND, D., MARCHAL, W., WATHEN, S. (2015), Statistical Techniques in Business and Economics, (16th Edition). McGraw-Hill Education. ISBN-13: 978-0078020520.

D: TRIOLA, M., F. (2015), Essentials of Statistics (5th Edition), Pearson Education. ISBN-13: 978-0321924599.

Requirements to the exam -
Last update: Koťátková Stránská Pavla Ing. Ph.D. (13.09.2023)

After receiving credit, the student may register for the examination. The examination will be written, at pre-announced times.

Students must register for the selected date in SIS. The exam lasts 90 minutes and has a maximum length of 90 minutes.

The score is 100. The exam will consist of two parts - a theoretical part (maximum 50 points) and a part that consists of two parts.

the practical part (maximum 50 points).

In order to pass the exam, the student must score at least 25 points out of the following in each of the two parts.

Syllabus -
Last update: Koťátková Stránská Pavla Ing. Ph.D. (13.09.2023)

1. Introduction to Statistics. Types of data, data representation and visualization.

2. The essentials of probability theory. Random Experiments, Sample space, Events, Probabilities.

3. Axioms of probability. Elementary probability theorems, conditional probability, multiplication rule. Subjective probability.

4. Random variable and probability theory. Random variable, frequency, probability distribution and its representation and main characteristics. Probability function, density function, cumulative distribution function and their properties.

5. Selected probability distributions I. Discrete random variable.

6. Selected probability distributions II. Continuous random variable.

7. Multidimensional random variable. Random vectors and multivariate probabilistic distributions.

8. Joint, marginal and conditional probability. Independence.

9. Storing data in random variables, introducing descriptive statistics, characteristics of location and of variability, central moments. Variance decomposition.

10. Introduction to statistical inference. From understanding a sample to assessing population. Point and interval estimates.

11. Statistical inference continued. Hypothesis testing: null and alternative hypothesis, level of significance, critical values and rejection interval, type I and type II errors, p-value, one-sided and two-sided alternative hypothesis.

12. Basic parametric tests: equality of mean, variance, one-sample or two-sample tests.

13. Introduction to non-parametric testing. Importance of normality. Assigning ranks. Selected non-parametric tests: Mann-Whitney, Wilcoxon rank-sum, sign test.

14. Final recap, consultations.

Course completion requirements -
Last update: Koťátková Stránská Pavla Ing. Ph.D. (13.09.2023)

The student will receive credit for attendance, activity in the exercises and completion of the credit written work for a minimum of 50% of all parts.

After receiving credit, the student may register for the examination. The examination will be written, at pre-announced times.

Students must register for the selected date in SIS. The exam lasts 90 minutes and has a maximum length of 90 minutes.

The score is 100. The exam will consist of two parts - a theoretical part (maximum 50 points) and a part that consists of two parts.

the practical part (maximum 50 points).

In order to pass the exam, the student must score at least 25 points out of the following in each of the two parts.

Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 2 56
Příprava na zkoušku a její absolvování 2 56
Účast na seminářích 1 28
6 / 6 168 / 168
Coursework assessment
Form Significance
Regular attendance 10
Examination test 70
Continuous assessment of study performance and course -credit tests 20

 
VŠCHT Praha