The course gives a deep understanding of the fundamentals of theory of measurements, as well as the theoretical approaches to the error analysis and the calculation of the values, parameters and predicted values according to the weighted functions. The students will have ability to analyse the results obtained in real measurement situations and practical skills to perform the necessary calculation for the determination of the most probable value and associated uncertainty.

1. Recall diferent contributions to the uncertainty of measurement
2. Estimate uncertainty of measurement for uncorrelated quantities
3. Employ Gauss distribution for determination of expanded uncertainty
4. Analysis of indirect and conditional measurements
5. Create self-developed algorithms for regression functions
6. Assess different approaches in the estimation of measurement results

Lectures to the group of students.

Mid-term exam and final exam.

The time-schedule for lectures will be used.

Additional explanations to students.

1. Data Measurement. Fields: monitoring, research, development, measurement, control. Introduction to analysis of measurement data.
2. DMS (Data Measurement System): definition, structure, outer and inner limits, classification according to the information and energy. Experiment. Fundamentals and terms (requirements, limits, repeatability). Carrying out of an experiment and records.
3. Mathematical model of measurand. Uncertaint of measurement - concept and contributions.
4. Correlated and non-correlated quantities. Effective level of freedom and level of confidence.
5. Error analysis. Direct measurements and weighted factors.
6. Laboratory methods of measurements and examples of determination of uncertainty of measurement.
7. Interlaboratory comparisons and determination of reference value.
8. Mid-term exam.
9. Quantities measured indirectly. Weighted regression functions, uncertainty of parameters. Application of matrix in the error analysis. Uncertainty of the predicted value.
10. Conditional measurements and conditional equations. Calculation of corrections.
11. Statistical functions and computer programs.
12. Usporedba više mjernih nizova i analiza varijance (ANOVA metode).
13. Parameters of real measurements (final resolution, hysteresis, arithmetic of final precision, non-corrected values). Rejection of result according to Chauvenet criterion.
14. Advanced techniques for analysis of results of measurement.
15. Final exam