VSFS:BA_PrSt Probability and Statistics - Informace o předmětu

BA_PrSt Probability and Statistics

Rozsah

2/1/0. 12 hodin KS/semestr. 6 kr. Ukončení: zk.

Vyučující

Ing. Hana Lipovská, Ph.D. (cvičící)

Garance

PaedDr. Renata Majovská, PhD.
Katedra informatiky a matematiky (FES, KIM) – Katedry – Vysoká škola finanční a správní
Kontaktní osoba: Bc. Kamila Procházková

Rozvrh seminárních/paralelních skupin

BA_PrSt/cECMCPH: každé sudé pondělí 15:45–16:29 E305, každé sudé pondělí 16:30–17:15 E305, H. Lipovská
BA_PrSt/pECMCPH: každé liché pondělí 12:15–12:59 E307, každé liché pondělí 13:00–13:45 E307, každé liché pondělí 14:00–14:44 E307, každé liché pondělí 14:45–15:30 E307, kromě Po 24. 10. ; a Po 24. 10. 12:15–13:45 E230, 14:00–15:30 E230, H. Lipovská

Předpoklady

There are no prerequisites for this course.

Omezení zápisu do předmětu

Předmět je otevřen studentům libovolného oboru.

Cíle předmětu

After completing the course students will be able to use basic terms of descriptive statistics. They will understand the problems of statistical surveys and will be able to process data. They will know the differences between simple and interval frequency distribution and they will also recognizes, in which case the simple frequency distribution is used for representation of the frequency distribution and in which case the interval frequency distribution (including graphical representation of the frequency distribution). Students will be able to measure the location, variability, skewness and kurtosis of frequency distribution.
They will be able to use the basic terms of probability theory, calculate the empirical and theoretical probability, create tree diagrams, Venn diagrams, use properties of probability numbers, the Law of large numbers. In the field of random variable, students will know some discrete probability distributions.

Výstupy z učení

After completing the course, a student will be able to:
- process and analyse quantitative and qualitative data,
- find characteristics of location and variability, coefficient of correlation,
- calculate probability.

Osnova

• 1. Definition of Statistics, Data sets, Branches of Statistics
• 2. Data classification, Data collection and design of a statistical study
• 3. Descriptive Statistics: Data processing of verbal variable
• 4. Data processing of numerical variable (a small data set), Measures of central tendency, variability, Quantiles
• 5. A frequency distribution, Intervals
• 6. Location characterizing of values of numerical variable (a large data set)
• 7. Variability characterizing of values of numerical variable (a large data set), The Empirical rule and Testing for Normality, Chebyshev’s theorem
• 8. Concentration characterizing of values of numerical variable
• 9. Bivariate data, Linear correlation, Linear regression
• 10. Probability: Probability of an event, empirical, theoretical, subjective probability, Properties of probability numbers, Law of large numbers
• 11. Conditional probability, Rules of probability, Mutually exclusive events, Independent events
• 12. Random variable, a distribution of discrete type

Literatura

povinná literatura
• Frost, J. Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries. Statistics By Jim Publishing, 2020. ISBN 978-1735431109.
• ZÁŠKODNÝ, Přemysl. The Principles of Probability and Statistics (Data Mining Approach). Praha: Curriculum, 2012, 122 s. ISBN 978-80-904948-6-2. info
• Hossein Pishro-Nik. Introduction to Probability, Statistics, and Random Processes. New York: Karra Research LLC, 2014. 731 s. ISBN 978-0990637202.

doporučená literatura
• Triola, M. Elementary Statistics. Pearson, 2017. ISBN 978-0134462455.
• Rumsey, D. J. Statistics For Dummies. For Dummies, 2016. ISBN 978-1119293521.

Výukové metody

Lectures and seminars in full-time study; tutorials in part-time study, MS Excel will be presented to the students. Minimum mandatory attendance at seminars in full-time is 75 %, the controlled group consultations in combined studies 50 %. Students who fail to meet the mandatory level of participation can be given additional study obligations. Students with ISP have the same duties. Compulsory attendance is not required.

Metody hodnocení

Credit:
- 1 written test, it is necessary to obtain at least 50 % of points from the test;
- 1 semester work from the area of descriptive statistics, it is needed to obtain at least 75 % of points;
Exam:
- 1 written test, it is necessary to obtain at least 60 % of points from the test;
- oral examination: student will answer 2 theoretical questions;

Vyučovací jazyk

Angličtina

Další komentáře

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