Errors caused by serious malfunctioning of instruments will generally be discovered because they create unbelievable results. Small deviations are much more difficult to detect. Sections 6.4.2 and 7.6 dealt with aberrant processes taking place at high count rates and discussed preventive measures. The effect of noise, another instrument distortion, has been discussed in Sections 6.4.5 and 7.7.4. Still another deviation from the true results caused by instruments may be introduced by the scaler (see Sect. 2.3.5). The time base (Sect. 11.2.1) which opens and closes the counting gate can be coupled to the line frequency, and fluctuations in this will be reflected in the results obtained.


Count Rate Background Activity Sample Activity Counting Efficiency Counting Gate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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References and Notes

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    M. R. Spiegel, Theory and Problems of Statistics, Schaum Publishing Company, New York (1961). An easily understood book on statistics.Google Scholar
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    Hewlett-Packard Company, Statistical Comparison of Digital System and a Ratemeter for Nuclear Measurements, Application Note 79, Palo Alto (1966). Discusses accuracies obtainable with a scaler and a ratemeter.Google Scholar
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    G. I. Coats, Absolute counting using the zero probability analysis, IEEE Trans. Nucl. Sci. NS-13:301 (1966). Instrumental and statistical discussion of a method to count the absence of pulses.ADSCrossRefGoogle Scholar
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    K. G. Proges, C. J. Rush, and G. E. Caya, Reduction of processing losses in on-line or off-line acquisition of random counts at high rates, Nucl. Instr. Meth. 78:115 (1970). Discusses the effect of a four-way parallel counter on dead time losses.CrossRefGoogle Scholar
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    E. Tanaka, Optimum window setting in a spectrometer for low-level activity counting, Int. J. Appl. Rad. Isotopes 16:405 (1965). Graphical method to adjust window width.CrossRefGoogle Scholar
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    S. Sterlinski, The lower limit of detection for very short-lived radioisotopes used in activation analysis, Nucl. Instr. Meth. 68:341 (1969). Discusses the point that the difference between Poisson distributions is not Poisson, but more complex.CrossRefGoogle Scholar
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    W. L. Nicholson, Statistics of net-counting-rate estimation with dominant background corrections, Nucleonics 24:118 (August 1966). Deals mainly with the problem of determining whether a certain amount of activity is present.Google Scholar
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Copyright information

© Plenum Press, New York 1973

Authors and Affiliations

  • Jan Krugers
    • 1
  1. 1.IBM—NetherlandsThe HagueThe Netherlands

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