Applied Statistics - AB413003
Title: Applied Statistics
Guaranteed by: Department of Mathematics, Informatics and Cybernetics (446)
Faculty: Faculty of Chemical Engineering
Actual: from 2021
Semester: summer
Points: summer s.:4
E-Credits: summer s.:4
Examination process: summer s.:
Hours per week, examination: summer s.:1/2, C+Ex [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Additional information: http://I.
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Zikmundová Markéta Mgr. Ph.D.
Šnupárková Jana RNDr. Ph.D.
Kříž Pavel Ing. Mgr. Ph.D.
Class: Předměty pro matematiku
Pre-requisite : {prerekvizita pro předmět Aplikovaná statistika}
Interchangeability : B413003, N413004, N413004A, N413504, S413004
Is interchangeable with: B413003
Examination dates   
This subject contains the following additional online materials
Annotation -
The Elementary Course of Statistics is aimed at undergraduate students. Students will learn basic statistical methods and gain insight into basic probability concepts. Data processing will be done using R software which is a programming language designed especially for statistical calculations and graphical outputs. It is a free software with quality help, and thanks to its great popularity in the statistical community, many blogs with tutorials, hints and sample examples can be found.
Last update: Zikmundová Markéta (03.06.2019)
Aim of the course -

Students will:

1. master fundamental statistical and probability concepts

2. have working knowledge of elementary statistical methods

3. be able to solve elementary statistical problems arising in applications

Last update: Kubová Petra (22.01.2018)
Literature -

R: S.M. Ross: Introduction to Probability and Statistics for Engineers and Scientists (2014, Elsevier)

R: J.I. Barragués: Probability and Statistics – A didactic Introduction (2014, Taylor & Francis)

R: B. Bowerman, R.T. O'Counel: Applied Statistics (1997, IRWIN Inc Company)

Last update: Šnupárková Jana (09.05.2019)
Learning resources -

Last update: Šnupárková Jana (18.09.2020)
Requirements to the exam

The rules for granting the credit are determined by the teachers. As a rule, it is necessary to actively participate in seminars and solve individual tasks, or successfully pass an additional comprehensive test. Attendance at seminars is mandatory.

The obtained credit is a necessary condition for passing the exam. The exam is oral.

Last update: Šnupárková Jana (18.09.2020)
Syllabus -

1. Random events, probability and its properties, independence of random events, conditional probability

2. Random variables, their probability distribution and characteristics

3. Fundamental types of probability distributions (especially normal distribution)

4. Random vectors and their distributions, correlation and independence of random variables

5. Sum of large number of random variables — Central Limit Theorem, Law of Large Numbers

6. Random sample, point estimate of expectation and variance, Maximum Likelihood and Bayesian estimators

7. Confidence intervals — calculation and interpretation

8. Testing of statistical hypotheses — basic principle, type I and II errors, interpretation of results (p-value), basic parametric and nonparametric tests


10. Test of independence of quantitative random variables (correlation test)

11. Goodness-of-fit testing, test of independence in contingency tables

12. Fundaments of regression analysis — linear, multiple, nonlinear

Last update: Šnupárková Jana (09.05.2019)
Entry requirements -

Students are expected to have either completed the prerequisite course Mathematics B or possess the equivalent knowledge prior to enrolling in the course.

Basic knowledge of calculus (derivatives and integrals, ideally also for functions of two variables), basic elements of set logic (Venn diagrams) and combinatorics are recommended.

Last update: Řehák Karel (07.03.2023)
Registration requirements -

Mathematics A

Last update: Borská Lucie (03.05.2019)
Course completion requirements -

Credit for controlled individual work. Oral exam.

Last update: Šnupárková Jana (18.09.2020)
Teaching methods
Activity Credits Hours
Účast na přednáškách 0.5 14
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Příprava na zkoušku a její absolvování 1.5 42
Účast na seminářích 1 28
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