Using the Log-Normal Distribution in the Statistical Treatment of Experimental Data Affected by Large Dispersion

There are situations in experimental work where large fluctuations of the measurand are experienced, either because of inherent variations of the observed quantity or because of the complexity of the system process leading to the output quantity. A large spread of the measured values around the center value results. It often appears to the experimenter that the spread of values around the mean is not symmetric, rather, values above the mean obtained by multiplying by a certain factor are approximately as likely as those obtained by dividing the mean value by the same factor. A log-normal distribution thus appears to be a candidate for a representation of the distribution of the observed quantity, at least as a simplifying assumption, when such distribution cannot be assumed a priori on the basis of physical reasoning. A system where large variations of the observed quantity result can be exemplified by the radiator-to-receiver transmission in the dominant presence of reflecting surfaces, such as in a screened room. Overall, large variations are often observed in EMC work, where we are usually faced with complex experimental or predictive processes. In the following, we describe the procedure through which the parameters of the log-normal distribution fitting a given set of experimental outcomes are obtained. This description is applied to the measured field distribution in a screened room.