Sometime back I gave a talk on the topic **‘Why Statistics?**’ in the course of a workshop on **Clinical Research Methodology**. Having found no crisp answers to the question during the research for the talk, and considering the importance of the topic, I thought **‘Why Statistics?’** would also be a good theme for a first blog post.

‘Statistics’ is a term used to refer both to the subject of statistics as well as to data and data summaries. I plan to discuss these different definitions of ‘statistics’ in a future post.

Statistics is a scientific discipline that is important not just in clinical research. Nowadays, with the increased emphasis placed on data analytics and evidence based decisions in research and business, an awareness of the importance and the right use of statistical methods becomes crucial in every domain of application.

As a scientific discipline, statistics can be defined as “*the science of collecting, analyzing, presenting, and drawing inference from data*”.

We should probably rewrite this definition as “…drawing inference from *incomplete *data”, because most often we use data from a random sample of a large population to draw conclusions about the population. Moreover, since different random samples drawn from the same population may give slightly different results due to the *sampling variability*, the definition of statistics can be further expanded as “the science of collecting, analyzing, and drawing inference from incomplete data,* in the presence of variability*”.

Why do we need to have a basic understanding of statistics?

Nowadays, in our professional as well as personal lives, we are constantly bombarded with ‘statistics’ (here statistics = data + analysis) in the course of our work or by the media.

We need to get a good understanding of statistics so that we are in a position to critically look at the origin of the data (design of study), the data themselves, the analysis of the data and the inference. Most importantly, we also need to know that, due to the sampling variability, there is will always be a certain amount of uncertainty in the inference from a statistical analysis. We need to keep this uncertainty in mind to take appropriate informed decisions. Unfortunately, most often, this uncertainty, either does not find its way into reports, especially, media reports or is not given sufficient importance (Nice cartoon at http://adequatebird.com/wp-content/uploads/2010/01/phd012010s.gif posted in The LoveStats Blog)

To put in a nutshell, a right understanding of the science of statistics is essential to filter the truth from the lies and the damned lies!