Lecturer(s)


Dostálková Iva, doc. RNDr. Ph.D.

Course content

Content of lectures: 1. Combinatorics 2. Discretete probability, 3. Axiomatic definition of probability, conditional probabilty. 4. Bayes Theorem, random variable. 5. Charakteristics of random variables. 6. Basis statistics. 7. chi^2 test 8. contingency tables 9. ttests 10. ANOVA 11. nonparametric tests 12. linear regression 13. nonparametric regression

Learning activities and teaching methods

Monologic (reading, lecture, briefing), Work with text (with textbook, with book)
 Preparation for classes
 28 hours per semester
 Preparation for credit
 28 hours per semester
 Preparation for exam
 28 hours per semester
 Class attendance
 28 hours per semester

Learning outcomes

Students master basic principles of probability and statistics.
Probability theory. The basic statistical methods

Prerequisites

basic mathematics

Assessment methods and criteria

Written examination
To complete the course it is necessary to pass the credit and pass the exam. To gain credit, sufficient attendance at the exercises and sufficient average success rate (50%) in short practice tests. Credit is a prerequisite for the exam test. The exam is written and is successful in reaching 50% of the test.

Recommended literature


http://cast.massey.ac.nz/collection_public.html.

Sokal, R.R., Rohlf, F.J. : Biometry. 3rd ed., San Francisco, Freeman and Comp., 1995.

Zar, J.H.: Biostatistical analysis. 2nd ed., Engelwood Cliffs Prentice  Hall,1984.
