Statistics and Results Evaluation

Vztahy:

In order to register for the course F7PMLAS, the student must have successfully completed or received credit for and not exhausted all examination dates for the course F7PMLSVV.

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Biomedical Technology

Synopsis:

The aim of the course is to get acquainted with the basic concepts of probability theory and mathematical statistics. The student is introduced to the probability model, the basic definitions of Kolmogorov's theory of probability and inductive statistics. They can apply these definitions to practical problems that arise in other areas of professional work and can explain them sufficiently (for example, doctors), they are familiar with the basic methods of inductive statistics and they can choose a suitable method for standard statistical problems.

Requirements:

The form of verification of study results: the exam is oral – 2 open questions focused on the issues discussed in the lectures.

Student requirements: for credit (credit is a necessary condition for taking the exam):

• obtaining at least 75% of the total number of points in 3 continuous written papers including typical examples from exercises;

• 3 absences per semester are allowed;

• active participation in exercises and homework is required.

Syllabus of lectures:

1. Motivational lecture. Determinism and randomness.

2. Random variable and its distribution function.

3. Discrete distribution.

4. Continuous distributions.

5. Random vectors, conditioning and independence.

6. Random vectors, numerical characteristics, functions of random variables.

7. The role of mathematical statistics.

8. Parameter estimates. Point estimates of basic characteristics, interval estimates for normal distribution.

9. Methods of construction of point estimates, method of moments, method of maximum likelihood. Introduction to Bayesian Statistics.

10. Tests of hypotheses in the normal distribution (one or two samples).

11. Analysis of variance (single and double sorting).

12. Tests about the type of distribution, normality testing.

13. Non-parametric tests.

14. Repetition.

Syllabus of tutorials:

1. Classical and geometric probability.

2. Combinatorial tasks.

3. Discrete quantity.

4. Continuous quantity.

5. A quantity with a normal distribution.

6. Conditional and marginal distribution.

7. Bayes theorem.

8. Point estimation of parameters.

9. Interval parameter estimation.

10. One-sample hypothesis test.

11. One-Sample Hypothesis Test of the Mean Versus the Estimation Interval.

12. Two-sample and paired hypothesis test about the mean.

13. Non-parametric tests. Chi-square hypothesis tests.

14. Repetition.

Study Objective:

Study materials:

Probability and statistics EBook [online]. USA, University of California, 2005 [cit. 2019-03-16] Poslední aktualizace [2014-03-09]. Dostupné z: http://wiki.stat.ucla.edu/socr/index.php/EBook

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Biomedical Laboratory Methods (compulsory course)