Description:

Random sample. Idea of statistical inference. Random variables and their distribution. Normal distribution. Central limit theorem. Multiple distribution. Independence. Correlation. Theory of estimation. ? point and interval estimate. Hypotheses testing. Test statistic and statistical decision. P-value. Simple linear regression ? parameters estimation, hypotheses testing, prediction intervals, regression diagnostic. Simulation independent realizations of random variables.

Contents:

1. Basic ideas of statistical inference.
2. Basic notions of probability calculus.
3. Discrete and continuous random variables and its distribution.
4. Multivariate distrbutions and estimation of their parameters.
5. Hypotheses testing (one-sample and two sample problems), one-way analysis of variance. Goodness of fit tests.
6. Linear regression.
7. Generation of several types of random variables. Method of inverse transformation.
8. Application to assessing structure reliability

Recommended literature:

Jay L. Devore: Probability and Statistics for Engineering and the Science, Duxbury

Abbreviations used:

Semester:

• W ... winter semester (usually October - February)
• S ... spring semester (usually March - June)
• W,S ... both semesters

Mode of completion of the course:

• A ... Assessment (no grade is given to this course but credits are awarded. You will receive only P (Passed) of F (Failed) and number of credits)
• GA ... Graded Assessment (a grade is awarded for this course)
• EX ... Examination (a grade is awarded for this course)
• A, EX ... Examination (the award of Assessment is a precondition for taking the Examination in the given subject, a grade is awarded for this course)

Weekly load (hours per week):

• P ... lecture
• C ... seminar
• L ... laboratory
• R ... proseminar
• S ... seminar