S2 = variance data m = Data average. If the number of samples is large The following equation is used: observed K square χ2= = degrees of freedom (n-1) υ If the numerical value of the parameter Z is between 1/ 96 and -1/ 96, As a result, the null hypothesis that the data follow from random distribution is confirmed. Otherwise, if I <1 or I> 1, the spatial distribution will be respectively cumulative and uniform. (Greco et al., 1999) Table 1: Average population in Pulvinaria aurantii in date of sampling : Egg Bag Nymph 1 Age Nymph 2 Age Nymph 3 Age 92/3/16 2/85 7 0 0 92/3/23 1/45 2/85 0 0 92/3/30 1.6 1/45 0 0 92/4/7 0/65 6/4 0 0 92/4/15 0/4 3/65 0 0 92/4/23 0.1 1/4 0/15 0/15 92/4/31 0/2 0 0 0/05 92/5/8 0.05 0/55 0/1 0/05 92/5/16 0.25 1/6 0/1 0
S2 = variance data m = Data average. If the number of samples is large The following equation is used: χ2= observed K square υ = degrees of freedom (n-1) If the numerical value of the parameter Z is between 1/ 96 and -1/ 96, As a result, the null hypothesis that the data follow from random distribution is confirmed. Otherwise, if I <1 or I> 1, the spatial distribution will be respectively cumulative and uniform. (Greco et al., 1999) Table 1: Average population in Pulvinaria aurantii in date of sampling : Nymph 3 Age Nymph 2 Age Nymph 1 Age Egg Bag 0 0 7 2/85 92/3/16 0 0 2/85 1/45 92/3/23 0 0 1/45 1.6 92/3/30 0 0 6/4 0/65 92/4/7 0 0 3/65 0/4 92/4/15 0/15 0/15 1/4 0.1 92/4/23 0/05 0 0 0/2 92/4/31 0/05 0/1 0/55 0.05 92/5/8 0 0/1 1/6 0.25 92/5/16
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