医用物理学实验

作者简介

医用物理学实验（英文版），ISBN：9787040355291，作者：刘志成 编

书籍目录

Introduction to Physics Experiments Introduction to Data Analysis Experiment 1 Measurement of Lengths Experiment 2 Operation of Dual Trace Oscilloscope Experiment 3 Measurement of Velocity and Acceleration of A Glider on An Air Track Experiment 4 The Measurement of the Young Modulus of Steel Experiment 5 Measurement of the Speed of An Ultrasonic Wave Experiment 6 Transient and Steady-State Process of RC Circuit Experiment 7 Experiment on Optical Interference and Newton ring Experiment 8 The Simulation of Electrostatic Field Experiment 9 Measurement of the Magnetic Field

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《医学教育改革系列教材:医用物理学实验(英文)》可供高等医学院校本科生、专科生各专业使用或参考学习。

章节摘录

版权页：   插图：   Sampling method--the measurements you make must be properly repre-sentative of the quantity you are trying to assess. If you were to find the di-ameter of a steel wire, you should not measure it at one position and orien-tation. If you are going to take samples from a production line for measure-ment, do not always take the first ten made on Wednesday afternoon. The environment--temperature, air pressure, humidity and many otherconditions might also affect the measuring instrument or the item beingmeasured. Whenever the size and effect of an error are known (e. g. from a cali-bration certificate), a correction should be applied to the measurement re-sult. However, in general, uncertainties from each of these sources, andfrom other sources, would be individual 'inputs' contributing to the overalluncertainty in the measurement. Based on the characteristics and the processing method, errors associ-ated the above mentioned sources of uncertainty can be classified into twocategories: systematic error and random error. Systematic error refers tothose caused by factors that affect the result in the same way for each of therepeated measurements (but you may not be able to tell). For example, er-rors associated with the measuring instrument and imported uncertaintymainly belong to this category. Systematic error can not be reduced by in-creasing the number of repeated measurements. In contrast, random errors are the those that take on random valueswhen repeating the measurement, and the uncertainty due to random errors canbe reduced by increasing the number of repetition of the measurement. Further-more, random errors generally tend to distribute in the same way, i. e. , theyusually obey normal or Gaussian distribution. You might see this type of distri-bution if you examine the heights of individuals in a large group of men.Most men are close to average height： few are extremely tall or short. A sketch of normal distribution is shown in Fig. 0. 2. Under normaldistribution, errors with small magnitude occur more frequently than thosewith large magnitude. In addition, the positive errors and negative errorsare symmetrically distributed about the center, where error is zero.

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