talk to each one with his/her own language.. every profession has a tongue.. for example you can talk with policy makers with change and amount of change, on the other hand economics can read estimated things and see the models for the future. Also physician interested in frequency and percent.... etc.

that is the point in all fields not only statistics (how the doctor can communicate with patients, how the teacher communicate with pupils and parents and so on)

talk to each one with his/her own language.. every profession has a tongue.. for example you can talk with policy makers with change and amount of change, on the other hand economics can read estimated things and see the models for the future. Also physician interested in frequency and percent.... etc.

that is the point in all fields not only statistics (how the doctor can communicate with patients, how the teacher communicate with pupils and parents and so on)

A very nice question. On a related topic, we are currently discussing how you actually explain what hypothesis testing and a significant result are in this thread: https://www.researchgate.net/post/How_would_you_explain_to_your_parents_hypothesis_testing_and_significance

Statistics often operate on large samples. It gives an overview and neglects details. You can compare this to looking at a forest from an airplane, from the above you do not see each tree clearly, but you can immediately see which part of the forest is abundant in water and which part is dry just by looking at the colours.

Looking at a small number of people only you may suspect that smokers more often have lung cancer, but then you also see other factors that may have contributed. Looking at a large group of people you will clearly see that lung cancer is more common among smokers, but it will require special effort to see how other factors may have contributed to the difference.

Statistics can also be seen as a way to quantify uncertainty. Often it is not difficult to tell the most likely difference between two groups (e.g. difference between average height of men and women); but to quantify how sure you can be that the real difference is near what you have seen in your sample is less easy. Statistics will tell you how precisely you can measure this difference on the strength of your data, also how much data you need to get a reasonably precise estimate.

Hello Heydar,

If you're really interested in examples of how statistics has shaped science and society, I strongly recommend the book "The Lady Tasting Tea - How Statistics Revolutionized Science in the Twentieth Century" by David Salsburg:

http://www.amazon.com/Lady-Tasting-Tea-Statistics-Revolutionized/dp/0805071342/ref=sr_1_1?s=books&ie=UTF8&qid=1350458521&sr=1-1&keywords=the+lady+tasting+tea

The book contains lots of good examples and is a good read too!

First you should find a hot story related to the non-statisticians, if you could, you are luck. Then, explain the facts logically , or more luck give some hints for them.It's the core of a applied sciences: read story first then think and make solution by your profession.

Statistics is a tool to transform data to information and then take a decision

Statistics is the science of collecting, summarizing, presenting and interpreting data. It says how to use them to verify the research hypotheses. In case of medicine, biostatistician for the modern physician is a partner that on the one hand ensures proper conduct analyzes, interprets the results and verifies hypotheses, on the other hand he allows the development of research and diagnostic methods for the improvement of the quality of medical care. The presence of statistician in the research group allows for improvement of the quality of planning and implementation of research, as well as the optimization of financial resources.

Royal Statistical Society UK, get stats site has a good video to view

People relate best to statistics in the sports of their interest - cricket or football or ...

In a DNA fingerprinting workshop a few years ago, a participant said he felt put off when the statistics teacher talked of red and blue balls and putting them into urns because he was unable to relate it to his own subject - biology. We had enjoyed a musical concert the previous evening, so I said to him : just as many songs can be fitted to the same sequence of notes (raag in Indian music) many real life phenomena fit the same underlying statistical model. The urn model is one such, and is useful in analysing many apparently unrelated real life phenomena to extract new insights...