SubjectsSubjects(version: 956)
Course, academic year 2019/2020

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Applied Statistics - N413004A
Title: Aplikovaná statistika
Guaranteed by: Department of Mathematics (413)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2019
Semester: winter
Points: winter s.:4
E-Credits: winter s.:4
Examination process: winter s.:
Hours per week, examination: winter s.:1/2, C+Ex [HT]
Capacity: 64 / 64 (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
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: Šnupárková Jana RNDr. Ph.D.
Zikmundová Markéta Mgr. Ph.D.
Class: Předměty pro matematiku
Interchangeability : N413004, N413504
Is interchangeable with: N413004, B413003, AB413003
Examination dates   Schedule   
Annotation -
The Elementary Course of Statistics is aimed at undergraduate students. Students will learn basic statistical methods and gain insight into basic probability concepts.
Last update: TAJ413 (17.12.2013)
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: TAJ413 (17.12.2013)
Literature -

R: Bowerman B., O`Counel R.T.: Applied Statistics, IRWIN Inc Company 1997, ISBN 0-256-19386-X

R: Freund J.E., Walpole R.E.: Mathematical Statistics, Prentice-Hall,Inc.,Englewood Cliffs, N.J., 1980

Last update: TAJ413 (17.07.2013)
Learning resources -

Last update: Šnupárková Jana (11.04.2016)
Syllabus -

1. Probability of random events, independence of random events.

2. Conditional probability, law of total probability, Bayes's theorem.

3. Random variable, distribution function, probability function, density.

4. Mean, variance, quantiles, median, critical values, independence and correlation of random variables.

5. Fundamental types of discrete and continuous distributions.

6. Random sample, sample statistics.

7. Point estimates, confidence intervals.

8. Testing of statistical hypotheses, type I and II errors. One-sample tests about mean and variance.

9. Two-sample tests about means and variances.

10. Independence testing.

11. Goodness-of-fit testing.

12. Contingency tables.

13. Fundamentals of regression analysis.

14. Summary, alternatively more specific statistical methods.

Last update: Šnupárková Jana (11.04.2016)
Registration requirements -

Mathematics I

Last update: TAJ413 (17.07.2013)