Entry requirements

Calculus.

Aims

To give basic knowledge of the theory of probability and of concepts and methods of statistical theory and their applications, especially in experimental investigations and statistical quality control.

Content

The course consists of two parts: Probability

theory and Statistical theory and methods.

Probability theory:

The probability concept. Sample space. Axioms of

probability. Random phenomena. Conditional

probability. Independent events. Random variables

and vectors. Distribution functions. Probability

distributions and density functions. Conditional

distributions. Independent random variables.

Expectation and variance. Special distributions:

The Binomial, Poisson and normal distributions.

Functions of random variables. The law of large

numbers. The central limit theorem. The Poisson

process.

Statistical theory and methods:

Elements of statistical investigations.

Descriptive statistics. Confidence intervals.

Hypothesis testing. Statistical inference for

normal distributions. Analysis of variance for

one-way classification. Regression analysis.

Elements of non-parametric statistics.

Statistical quality control. Experimental

design.

Instruction

Lectures and problem solving sessions.

Assessment

Written examination at the end of each sub-course.

Compulsory assignments may be given during the

course.