Statistics is a crucial tool in pharmacological research that's wont to summarize descriptive statistics experimental data in terms of central tendency but more importantly it enables us to conduct hypothesis testing. Therefore, it is essential for pharmacologists to have an understanding of the uses and abuses of statistics. With this in mind,
Pharmacology routinely employs statistics to help summarize data and, more importantly, to test hypotheses. This is a relatively simple matter when one is only interested in testing the Null hypothesis that two sample means are equal However, this type of experimental design and hence analysis does have a number of limitations.
If you are confused about the most appropriate statistics for your experiment, you could simply talk to a statistician. However, it is clear that statisticians and pharmacologists often speak a different language. The statistician deals with uncertainties and calculates the probability of a particular event simply occurring by chance, and that is before you try and grasp the mathematics. In general, pharmacologists like to deal with certainties, Better experimental design is one potential benefit from learning the language of statistics. The majority of scientists do not set out to undertake clinical trials in animals per se. Rather, we test the hypothesis that drug treatment may or may not alter a biological response, which mimics some feature of the disease process we are studying. The so-called ‘clinical trials' in animals are for all intent and purposes, proof of concept studies, which might give one confidence to proceed with the particular drug target of interest in man.