Compilation of measurement results
Objectives of the course:
- Knowledge about compiling measurement results.
- Proper presentation and interpretation of measurement results.
- Specification of measurement accuracy.
- Specification and improvement of measurement procedures.
- Knowledge of statistical instruments for measurement data processing.
- Formatting charts and using them in the process of inference.
See the laboratory
day 2, h. 9.00 - 16.00
- A certificate of completion
- Educational aids: scripts
- Access to specialist magazines and technical literature (regarding stationary training)
- Writing aids (pen, notebook) - regarding stationary training
- Complete care of idividually assigned customer service person
- Participant Cards with discounts to partner restaurants / pubs in Gliwice (regarding stationary training)
Please contact us on:
0048 32 4111 000
should you have any questions on the course you have chosen
- Notation and rounding of measurement results, errors and uncertainties
- General physical condition system
- Influence quantities and their analysis
- Significant and certain digits in measurement results
- Analysis of the spread of multiple measurement results
- Measurement method errors and possibilities of their compensation
- Interpretation of specifications of devices for precise measurements
- Philosophy of constructing statistical programs
- Regularity of actions, selection of terminology, nomenclature, result archiving
- Basic options of a statistical program for data processing
- Calculation arrangement with the use of measurement results
- Selection of forms and parameters for graphs
- Approximation and interpolation of distributed data
- Inference about complementing the research
- Selection of approximating functions
- Spline interpolation
- Calculating measurement uncertainty
- Calculating convolution of distributions, confidence intervals and confidence levels
- Analysis of program calculation limitations
- Compilation of different data according to various models
- Creating uncertainty budgets and inference about improvement of the experiment