Statistics 1 - AB501009
Title: Statistics 1
Guaranteed by: Department of Economics and Management (837)
Faculty: Central University Departments of UCT Prague
Actual: from 2022
Semester: winter
Points: winter s.:6
E-Credits: winter s.:6
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Koťátková Stránská Pavla Ing. Ph.D.
Is interchangeable with: B501009
Examination dates   
This subject contains the following additional online materials
Annotation -
In the Statistics I course, the students will learn basics of probability theory and statistics and will practice the theoretical concepts on various practical problems. The students will also learn about basics of data processing, presentation and interpretation. The course is a preparation for further exploration of statistical methods for elementary analysis of economic and social phenomena. The students will learn how to distinguish the situations and appropriate methods for given circumstances and types of data. A guidance to proper presentation and interpretation of the data and their results will be provided as well. Selected topics will be presented in the computing environments of MS Excel and Gretl.
Last update: Scholleová Hana (10.12.2021)
Literature -

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

R: TRIOLA, M., F. (2015), Essentials of Statistics (5th Edition), Pearson Education.

R: LEVINE, SZABAT, STEPHAN (2016), Business Statistics: A First Course. New York: Pearson Global Edition.

R: ZÁŠKODNÝ, Přemysl (2012), The Principles of Probability and Statistics (Data Mining Approach). Praha: Curriculum.

Last update: Krajčová Jana (15.09.2020)
Requirements to the exam -

After obtaining the credit, a student will be able to take the exam. The exam will be written, in pre-announced dates.

Students have to register for the chosen date in SIS. The duration of the exam is 90 minutes and the maximum

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

practical part (maximum of 50 points). To successfully pass the exam, a student needs to earn at least 25 points from

each of the two parts.

Last update: Koťátková Stránská Pavla (12.09.2023)
Syllabus -

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.

Last update: Scholleová Hana (10.12.2021)
Course completion requirements -

Credit can be awarded to student based on his participation in practical exercises and submitted homework during the semester. Alternatively student can pass a test at the end of the semester, with minimum required score of 60%. The minimum required attendance rate to seminars is 75%. The details will be agreed upon with the seminar instructor at the beginning of the semester.

A credit is required to allow a student to take the final exam. The final exam will cover both, the theory and the practical exercises. The exam will be in written form but can be complemented by oral examination.

Last update: Botek Marek (17.01.2020)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 2 56
Účast na seminářích 1 28
6 / 6 168 / 168
Coursework assessment
Form Significance
Examination test 80
Continuous assessment of study performance and course -credit tests 20