Statistical Models ?

As we have seen in class, statistics can be a great tool to analyze data and understand its behavior. A strong statistics background is useful no matter what you study.
The use of numerical data, can prodive us great insight on the nature of a system. For example, the mean, standard deviation and median are deeply useful in order to understand the distribution of our data.
When our data isnt enough, we can estimate the uncertainities and calculate whatever we need to estimate with an approximation.
When we are uncertain about the outcomes of a situatiion, we can estimate the probabilistic model of behavior using past information. For example, if we have seen there are dark clouds on the sky, we can imply from past behavior there is a high chance that it will rain.
We can also extrapolate data ( infer data outside of our range of data) and interpolate data ( infer data within our range of data) using linear regression systems that fulfill and intrincate, yet reliable mathematical approach to estimate data.
No matter what we do, our analysis will always require some kind of numerical or data analysis. The abillity to understand the limitations and capacities of statistical models is the first step toward a better analysis no matter the situation.