Understanding of Statistics in Testing of Pharmacological Hypothesis

Anoop Kumar, Neelima Sharma and Dinakar Sasmal *

Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi -835215, Jharkhand, India.

Correspondence: dsasmal@bitmesra.ac.in.


Statistics is an important tool in pharmacological research to conduct hypothesis testing. It is used to summarize experimental data in terms of central tendency (mean, median or mode) and variance (standard deviation, standard error of the mean, confidence interval).The purpose of statistical analysis is to determine whether the observed differences between the treated and untreated animals/humans could have arisen by chance or by the drug? Now days, there has been a huge increase in the use of statistics in pharmacological (preclinical and clinical) research, especially after the availability of user friendly statistical software. The biostatical tools give meaning to raw data generated during the research studies. Results of various statistics tests help to draw a valid conclusion from the observations. However, the basic understanding of methodology (study design, sample size justification and correct use of sampling techniques) and bio statistical tests (parametric and non–parametric tests) is still lacking among pharmacologists. Therefore, it is essential for every pharmacologist to have an understanding of the correct uses of statistics. Thus, in this review, we tried to simplify the understanding of statistical tool in pharmacology field.

Keywords: Null hypothesis, Alternate hypothesis, Type 1 error, Type 2 error, p-value, Power of study.

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