Sometimes in the process of statistical analysis, data should be normalized but which method is right?
Dear Dr. Roughani
Data transformations are an important tool for the proper statistical analysis of biological data. To those with a limited knowledge of statistics, however, they may seem a bit fishy, a form of playing around with your data in order to get the answer you want. It is therefore essential that you be able to defend your use of data transformations.
There are an infinite number of transformations you could use, but it is better to use a transformation that other researchers commonly use in your field, such as the square-root transformation for count data or the log transformation for size data. Even if an obscure transformation that not many people have heard of gives you slightly more normal or more homoscedastic data, it will probably be better to use a more common transformation so people don't get suspicious.
http://www.biostathandbook.com/transformation.html
There are many transformations that are used occasionally in biology; here are three of the most common:
1. Log transformation
2. Square-root transformation
3. Arcsine transformation
The following articles explain how to choose the correct data transformation method, which I hope will be useful to you.
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