#### How Statistics Plays A Key Role In Data Science? Explained

Everyone must be quite aware of the fact that Data Science is a comprehensive blend of maths, business & technology. The process of Data Science begins by interfering the data in hand & goes all the way to algorithm development & then it makes use of existing tools & technologies to draw the solutions for complex problems.

At its core, Data Science makes use of several mathematical applications for making accurate assumptions of data & helps in presenting the right value for the business enterprises. But have you ever wondered how simple mathematic concepts like statistics could play such a key role in the Data Science process?

If you are having the same doubt then let’s helps in clearing it.

Statistics In Data Science-

In several applications of Data Science you will be noticing that both statistics & computer science applications will be competing with each other. Let’s have a look at how different concepts in Statistics would be playing a key role in the Data Science process.

Probability Distributions-

The concept of Probability Distribution helps in a characteristic that helps in determining the likelihood that a random variable can take feasible values. This simply means that the variable values differ according to the fundamental spread of likelihoods.

This concept of distribution comes handy in Data Science process especially in the scenarios where we are required to find out outcomes with high likelihood & want to measure their predicted/potential values over a range

Dimensionality Reduction-

While dealing with the concept of Machine learning for classification problems, you should know that there are so many factors based on which the on final classification is done. These factors are nothing but characteristic variables. If the problem consists of too many characteristic variables then it becomes quite tough to visualize & operate. This is where Dimensionality Reduction comes to the play.

It helps in eliminating a large number of variables to reach a smaller subset or arriving at the variables which matter more than then others. This makes it easy to visualize & interpret with the problem.

Bayesian Statistics-

Bayesian Statistics will be playing a key role in the cases that involves random events. This concept helps in evaluating the confidence of the occurrence of a particular event by eliminating the uncertainty.

The other statistics applications that play a key role in the Data Science process are Over and Under-Sampling & Descriptive Statistics.

‘You should be clearly aware of the fact that statistics is just key player in the process of Data Science but not a sole player’

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