A common English quote says that there are three kinds of lies: lies, damned lies and statistics. This sentence was wrongly attributed to Disraeli, whereas it was firstly published by Marc Twain. Even if it could seem true, statistics is the only tool available up to date to manage a large amount of data and to give their a mean. Several functions are usually used in statistical analysis; the most common are the average, standard deviation, frequency and also the number of observation is reported in scientific publications.

All these data are defined as descriptive statistics because of their direct characterization of the population of interest. In other cases more complex calculations must be done to find significance from the study. Linear or logistic regressions are models to identify the trend that better explain and summarize the collected data. From linear or logistic regression is possible to interpolate or extrapolate data in order to predict results into the studied range or outside the studied range, respectively. Furthermore, from statistical analyses prevalence, incidence, absolute risk, odd ratio and relative risk are determined. All of these parameters are so important that must be determined during clinical study and are subsequently used to compare different protocols, drugs and so on. Clinical studies are classified as experimental studies or observational studies. The main difference between these two classes is the presence of a treatment given to patients in the experimental studies, whereas in the observational studies none treatment is followed but the selected population is just observed to determine the parameters of interest.

In both cases, given the high number of patients enrolled in order to obtain significant results, statistics is useful to compare treated cohort and placebo cohort, for example, as well as to evaluate the role of specific component of the study, namely called covariates. The major part of software that help to collect and manage data from a clinical study have also some algorithms to calculate standard statistical parameters during the data collection self. Revision and further elaboration must be done by professionals in order to correctly consider study results. Statistics is important not only in clinical trials, but also in all experiments performed in science. Indeed, to be sure to have obtained a result as a consequence of certain conditions and not due to serendipity, all experiments are usually repeated three or more times. Data presentation normally comprises average and standard deviation or confidence interval and significance is determined by a series of tests that should be described in material and methods section of the publication. In conclusion scientists must have some basis of statistics because this discipline confers value to their experiments and make them shareable and comparable with scientific community. Even if statistics is considered as a lie in some cases, it will be useful for science advances.