1. Purpose and content of the subject, requiements for obtaining the credit and passing the exam, information sources. Basics of combinatorics, prior and statistical probability, total and compound probability, independent and dependent repeated experiment. 2. Random variable discrete and continuous, probability distribution of random variable, probability density and cumulative distribution function, types of distribution, characteristics of position and variability. 3. Classification of measurement errors, Normal distribution, primary and selective characteristics of random variable array. 4. Two- and more-dimensional random variable – covariance, correlation coefficient, covariance and correlation matrix. Law of true errors propagation. 5. Law of standard errors propagation, application to sum/difference and mean, matrix notation. 6. Inverze task of law of standard errors propagation, principle of equal influence, law of standard errors propagation on function array. 7. Variable accuracy measurement, weights and cofactors, weight and cofactor matrix, law of weigths propagation. 8. Adjustment of redundant measurements, adjustment methods, Least squares method and it's applications. 9. Direct observations adjustment of equal and unequal accuracy. 10. Measurement pairs of equal and unequal accuracy.

1. Introduction, envelope, exercise Prior and statistical probability. 2. Test, exercise Repeated experiment. 3. Test, examples random variable, Normal distribution, Normal normed distribution. 4. Test, exercise Normal distribution. 5. Consultation of the exercise Normal distribution, spare. 6. Test, exercise Laws of errors propagation. 7. Test, exercise Law of standard errors propagation on function array. 8. Test, exercise Adjustment of direct observations and pairs of measurement. 9. Test, consultation and correction of all the exercises, spare. 10. Checking fulfilment requirements and granting credits.