# Why Statistics?

Take a look at the below advertising claim.

Nike claims that their Vaporfly shoes make a runner 4 percent more efficient, it claims a performance increase when you wear these pair of shoes. This is a big claim. But the main question is how was Nike able to make such a claim? On what basis? how was the research carried out? Oh, Nike must’ve asked a person to wear his regular shoes followed by these shoes and run equidistant laps and time differences were calculated right? NO, that would be a highly unreliable claim then. It is also not humanly possible to test these shoes on marathon runners across the globe. What Nike did is it used a random sample of the target population, amateur marathon runners, tested their product and calculated the mean, median of the time difference of the sample. Captured the latent measures of how people felt, drew correlations as to what will eventually make them efficient in the long run. No pun intended. Look at the below example for a pharmaceutical claim.

Here Dettol claims to kill 99.9% of all the germs. Here too the claim is purely based on observations on AB tests carried out by the company. The group of test subjects were recorded before and after the using the Dettol product and median or mean of the difference in presence of germs was calculated and those results were said to be between an interval of values with a confidence level of 95/99 % (We will discuss confidence intervals later).

Following are other examples where statistical research are used

1. In the food industry, an energy drink is claimed to boost your energy for the next 12 hours.
2. In the technology industry a microprocessor is claimed to squeeze out 20% more performance while consuming 10% less power than previous generation chips.
3. Due to a deadly pandemic of a certain disease the deaths are likely to be around 20k in next 2 months.
4. The temperature, humidity and wind flow shows the probability of rains in the next two days.

There are infinite examples where statistics is used. Also every claim made by humans is based on a statistical study and cannot be 100% accurate. The point I am trying to make is statistics is a powerful tool that helps us study and make inferences from the past data available and predict the future outcomes close to accurate values. This is extremely useful in decision making. All those pie charts, time series, pivot tables etc. are financial data visualizations in a business on which statistical tools would be applied to make the next revolutionary business decision. Statistics can be applied to your own life, like personal expenditure and financial growth once you get acquainted with the tools. I will make this beautiful subject as close to real life as possible while explaining the concepts. I will also drop in important links to articles/ books or code which I think you should refer.

Hi good to see y'all, I am an aspiring data analyst and will be posting stuff about Statistics, Python and R and also some interesting projects I do. B-)

## More from Jayesh Rao

Hi good to see y'all, I am an aspiring data analyst and will be posting stuff about Statistics, Python and R and also some interesting projects I do. B-)