Fundamentals of Data Analysis Lecture 2 Theory of error.

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Presentation transcript:

Fundamentals of Data Analysis Lecture 2 Theory of error

Program for today F Definition and types of errors; F Propagation of errors F Metrological characteristics of the mesurement unit; F Inference in the theory of errors;

Introduction The measurement of a physical quantity can never be made with perfect accuracy, there will always be some error or uncertainty present. For any measurement there are an infinite number of factors that can cause a value obtained experimentally to deviate from the true (theoretical) value. Most of these factors have a negligible effect on the outcome of an experiment and can usually be ignored. However, some effects can cause a significant alteration, or error, in the experimental result.

Introduction What is error theory? It is a theory of measurements. There are errors associated to instruments. There are errors associated with human beings. There are errors associated to our mathematical limitations.

Introduction The error is important to: The precision of the obtained results. The number of numbers that we should take into account To decide which could be the best measurement strategy

Sources of error Each experiment, each measure and almost every component of the measurement operation gives results subject to various types of errors

Definition of an error In mathematics, an error (or residual) is not a "mistake" but rather a difference between a computed, estimated, or measured value and the accepted, true, specified, or theoretically correct value.

Definition of an error Observational error is the difference between a measured value of quantity and its true value.

Definition of an error In science and engineering in general an error is defined as a difference between the desired and actual performance or behavior of a system or object.

Types of error There are many different types of errors that can occur in an experiment, but they will generally fall into one of two categories: n random errors n systematic errors.

Types of error n Random errors usually result from human and from accidental errors. Accidental errors are brought about by changing experimental conditions that are beyond the control of the experimenter u These fluctuations are taken into account with the absolute error ε. u There is another way to express the fluctuations with the magnitude called ε r.

Types of error n A systematic error is an error that will occur consistently in only one direction each time the experiment is performed, i.e., the value of the measurement will always be greater (or lesser) than the real value. Systematic errors most commonly arise from defects in the instrumentation or from using improper measuring techniques.

Types of error Division of errors due to physical causes of error: n calibration error n quantization error n unstability error n sampling error n counting error

Types of error Division of errors due to the measurement conditions: n intrinsic error (in reference, calibration conditions) n additional error (in other conditions)

Types of error Division of errors due to the nature of the measured value: n statical error n dynamical error

Types of error measure There are three types of error measure: n true errors, n conventionally true errors n boundary errors

Propagation of errors In many experiments, the quantities measured are not the quantities of final interest. Since all measurements have uncertainties associated with them, clearly any calculated quantity will have an error that is related to the errors of the direct measurements. The procedure used to estimate the error for the calculated quantities is called the propagation of errors.

Propagation of errors Addition and Subtraction Z = A+B or Z=A-B Multiplication and Division Z=A*B or Z=A/B

Metrological characteristic The concept of a metrological characteristics understood the full information on the errors of the measurement system presented in a structured way. The variety of instruments and a variety of their applications mean that there is no single way to develop metrological characteristics. While there are some normative recommendations, equipment manufacturers, however, use of different variants of the characteristics, simplifying them in a rather arbitrary manner.

Metrological characteristics Instability error probability distribution for oxygen analyzer

Metrological characteristic The course of instability error and its forecast Forecast of the error Confidence interval

Class of accuracy Class of accuracy is a figure which represents the error tolerance of a measuring device. The professional measuring devices are labeled for the class of accuracy. This figure is the percentage of the inherent error of the measuring device with respect to full scale deflection. For example, if the class of accuracy is 2 that means an error of 0,2 volts in a full scale 10 volt reading.

Inference in the theory of errors n Calibration is a comparison between measurements – one of known magnitude or correctness made or set with one device and another measurement made in as similar a way as possible with a second device. n The device with the known or assigned correctness is called the standard. The second device is the unit under test.

Inference in the theory of errors Calibration may be called for: n a new instrument n after an instrument has been repaired or modified n when a specified time period has elapsed n when a specified usage (operating hours) has elapsed n before and/or after a critical measurement n after an event, for example after an instrument has had a shock

Inference in the theory of errors Legalization of equipment is: n Set of activities including checking, declaration and verification statement of evidence that meets the requirements of a measuring instrument; n The activities carried out by the state legal metrology services in order to determine and certify that the measuring instrument meets the requirements of validation rules, consist of the examination and tools marking.

Inference in the theory of errors Adiustacją nazywa się wykonanie ściśle określonych stosowną instrukcją czynności regulacji (kalibrowania) układu pomiarowego, przy wykorzystaniu wzorca jako niezbędnego elementu pomocniczego, sprowadzające błąd do zadanej wartości (najczęściej do zera). Oczywiście, gdy np. przyrząd nie ma możliwości regulacji zamiast adiustacji można przeprowadzić zwykłe wzorcowanie.

Error function Jeżeli pomiary pewnej wielkości x narażone są na wpływ wielu niewielkich i przypadkowych zaburzeń, to rozkład wyników jest rozkładem normalnym. Całka funkcji gęstości prawdopodobieństwa opisującej rozkład normalny, oznaczana czasem jako erf(t) i obliczana zgodnie ze wzorem: nosi nazwę funkcji błędu lub normalnej całki błędu i określa prawdopodobieństwo tego, że wartość pomiaru znajdzie się w promieniu t odchyleń standardowych od wartości prawdziwej X.

Thank you for your attention !