Students are supposed to know:

Soft Competence:

1. To master fundamental statistical and probability concepts

2. Knowledge and acceptance of elementary statistical methods

Specific Competence:

3. To solve elementary statistical tasks with self-reliance

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)

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.

http://www.vscht.cz/mat/AS/TABLESANGL.pdf

Mathematics I