The process that human understands and transforms nature is the process of continuous measurement and study of various phenomena in the natural world. Through the analysis of the causes of errors, we can effectively eliminate or reduce the errors, and through the accurate processing of the measurement results, we can uncover the hidden objective laws behind the data. As a result, error theory and data processing have received increasing attention.

Error theory and data processing are not only the core basic courses of instrumentation disciplines, but also for human exploration and transformation of nature, the measurement data obtained by researchers of any discipline in the process of carrying out scientific experiments and engineering practices must be subjected to reasonable error analysis and data processing in order to give accurate evaluation to the measurement results and to obtain real scientific findings. Error theory and data processing have important supporting roles for these disciplines as well.

The course begins with the concepts of measurement, testing and metrology, through an introduction to the history of error theory and data processing. It helps to clarify the body of knowledge of the course. Considering the processing of parametric measurement results and the analysis and evaluation of test systems, which are two different applications, and focusing on static and dynamic measurements, as well as equal and unequal precision measurements, the knowledge points of the course are introduced in detail. By interspersing a large number of application examples, it helps you to accurately apply the knowledge points to solve practical problems in scientific research and engineering practice.

Learning "error theory and data processing" will not only enables us to understand the objective world more accurately, but also helps us get a golden key to open the door of the unknown world.

1. Master the basic concept and significance of error analysis, having the ability to analyze the error of measurement results independently.

2. Master the error analysis and compensation algorithm of the static measurement and dynamic measurement results of the test system.

3. Through the appropriate error compensation to improve the performance of the test system reasonable, having the ability to improve the test system design.

Advanced Mathematics for Engineering

Automatic Test Principles and Systems

Engineering Advanced Mathematics

Probability Theory and Mathematical Statistics

1. Zhen Qian, et. al. Error Analysis and Data Process (The 2nd Edition). Beijing: China Science publishing & Media Ltd., 202211.

2. John R. Taylor. An Introduciton to Error Analysis: The Study of Uncertainties in Physical Measurements. HEP Series in Mechanical Engineering Frontiers. University Science Books. 1997

3. Yetai Fei. Error Analysis and Data Process (The 6th Edition). Beijing: China Machine press, 2010.

4. Evaluation of measurement data-Guide to expression of uncertainty in measurement(GUM). JCGM, 2008.