SubjectsSubjects(version: 877)
Course, academic year 2020/2021
  
Applied Statistics - AB413003
Title: Applied Statistics
Guaranteed by: Department of Mathematics (413)
Actual: from 2020
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 [hours/week]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
Language: English
Teaching methods: full-time
Level:  
For type: Bachelor's
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 Mgr. Ph.D.
Kříž Pavel Mgr. Ing. Ph.D.
Class: Předměty pro matematiku
Interchangeability : B413003, N413004, N413004A, S413004
Z//Is interchangeable with: B413003
Annotation -
Last update: Zikmundová Markéta Mgr. Ph.D. (03.06.2019)
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.
Aim of the course -
Last update: Kubová Petra Ing. (22.01.2018)

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

Literature -
Last update: Šnupárková Jana Mgr. Ph.D. (09.05.2019)

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)

Learning resources -
Last update: Šnupárková Jana Mgr. Ph.D. (18.09.2020)

https://e-learning.vscht.cz/course/view.php?id=581

Requirements to the exam
Last update: Šnupárková Jana Mgr. Ph.D. (18.09.2020)

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.

Syllabus -
Last update: Šnupárková Jana Mgr. Ph.D. (09.05.2019)

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

9. ANOVA

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

Entry requirements -
Last update: Borská Lucie RNDr. Ph.D. (13.05.2019)

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

Registration requirements -
Last update: Borská Lucie RNDr. Ph.D. (03.05.2019)

Mathematics A

Course completion requirements -
Last update: Šnupárková Jana Mgr. Ph.D. (18.09.2020)

Credit for controlled individual work. Oral exam.

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
4 / 4 112 / 112
Coursework assessment
Form Significance
Oral examination 100

 
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