1. A Method of Separating Two Superimposed Normal Distributions using Arithmetic Probability Paper
- Author
-
D. Harris
- Subjects
Abscissa ,Convolution of probability distributions ,Standard deviation ,Normal distribution ,symbols.namesake ,Ordinate ,Line (geometry) ,symbols ,Animal Science and Zoology ,Frequency distribution ,Arithmetic ,Ecology, Evolution, Behavior and Systematics ,K-distribution ,Mathematics - Abstract
By using arithmetic probability paper a normal distribution can be transformed into a straight line by plotting cumulative frequencies, expressed as percentages of the total frequency as the ordinate, against the mid-point of the class intervals as the abscissa. From such a line both the mean and standard deviation can be obtained. The mean is the point on the abscissa corresponding to the position where the line intersects the 5000 ordinate and the standard deviation is the distance along the abscissa lying between the mean and a point corresponding to either 15.870% or 84 13% on the ordinate. Conversely, if the mean and standard deviation are known, a distribution can be represented as a straight line. Recently, from an investigation into the movements of coarse fish (Stott 1961, 1967), data were obtained on the frequency with which recaptures were made and the distance they had moved from a release point which, when plotted in the above manner on arithmetic probability paper, produced sigmoid curves similar to that labelled AF in Fig. 1. The data for Fig. 1 are given in Table 1, and for the purpose of illustration they are hypothetical. Since it can be demonstrated that this type of curve results if two straight lines, such as XX' and YY' in Fig. 1, are compounded, it seemed reasonable to interpret the data from the investigation as being the resultant of two superimposed normal distributions of differing dispersions. This led to the postulate that the fish populations studied were divisible into two components on the basis of their observed mobility and indeed subsequent laboratory work confirmed this hypothesis (Stott 1967). In order to estimate the proportion and parameters of the mobile and static sub-populations observed in the field, a search was made for a technique to separate these components. Methods of separating polymodal frequency distributions have been described by Harding (1949), Cassie (1954) and Tanaka (1962), the two former using arithmetic probability paper. However, their solutions seem only to be of use if the amount of overlap between distributions is small and a similar limitation applies to the cases referred to by Cox (1966). It appeared, therefore, that with superimposed distributions the only approach possible would be one of trial and error based on the fact that the less dispersed normal distribution (XX' in Fig. 1) does not overlap the other one to a significant degree at the tails of the resultant sigmoid. By trial and error the shallower line (YY' in Fig. 1) could be obtained by progressively reducing the values of the frequencies between the points where it was obvious that the two distributions were 'superimposed (i.e. between B and E on line AF in Fig. 1) until the data from this common portion of AF plus that from the two tails, AB and EF would form a straight line when
- Published
- 1968