VIEWING OUR DATA

The graphical representation of the data well resumes the differences between the two types of normalization. In each graph, we report the mean of three means of three experiments (E=Effect) as a function of the concentration of a generic toxicant. Two points are evident:

(1)   After normalization 1 (GREEN), Control has no error bar, because all the data are normalized to 1 experiment per experiment. After Normalization 2 (BLUE), the error bar on controls has the same relative amplitude of the non-normalized data (in RED).

(2)   The dispersion of data is higher after normalization 1 than normalization 2. It also justifies the difference in significances observed in our previous post. Why? The reason is that the elimination of  variability of controls, which is done with normalization 1, may increase the gap among experiments at the same condition, measuring a relative effect respect to control. And it may have an effect on the dispersion around the mean. This approach valorizes a difference in subjective susceptibility to a toxicant.

It should be noted that NORMALIZATION 1 is not WRONG a priori. However, the Researcher should clearly justify this approach. As already said, it may be used when each experiment represents a different subject/animal, and a background difference between each experimental unit may be canceled to assess the individual susceptibility to a toxicant. Other approaches may be used, and I will show them in the next episodes.