Table 8 shows the individual error percentage and mean absolute percentage error between experimental and response surface equations predicted values of thermo-physiological properties.
The MSE is an average of the squares of all the individual errors between the model and the real measurements.
When the pooled DLCV error is between the two individual errors, and lower/higher than the weighted mean (number of samples chosen as weights) we label the effect as marginal synergetic/marginal anti-synergetic.
It is obvious that there is a relationship between the two individual errors and the combined sum.
Viewed a different way, if one collapses the diversity in the different perspectives of individuals vs. the consensus of the crowd, one equally collapses the difference between the crowd error and the average individual error by forcing little or no difference between individuals.
This was achieved by testing the visual similarity between individual error responses (Type B and C) and (i) the averaged image of the flankers and target (to test the averaging account); or (ii) the images of the individual flankers and target items (to test the substitution account).
Specifically, if the crowd error differs from what the average individual error predicts vs. external truth, then there must be differences between what individuals predict amongst themselves (i.e., not perfect consensus).
This model decomposes the total variance into between-individual error (or bias) and within-individual error (or imprecision).
Furthermore, in the condition of Mitogen, the mean-square value directing the effect of ELISA, or "between-individual error", was significantly large (P = 0.017).
Herein, "between-individual error" indicates deviation in interferon-gamma values caused by the difference between Harvesters or ELISA operators, and "within-individual error" represents fluctuation of interferon-gamma values measured by a single Harvester or ELISA operator.
