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When we learn about mean, median, mode, range, variance, skewness of the data; we are essentially talking about Descriptive Statistics. It is undoubtedly first and best thing you can do when your mail box is hit with data from manager.

But todays post is going to be all about Inferential Statistics.

As Descriptive Statistics describes the data, inferential statistics finds metrics that samples can say about population. Basically what do we infer/generalize about the population of say 1 crore data points from just sample of say 1000 data points.

Yes, that’s what we are here for. Inferential Statistics is divided into two sub parts/techniques.

1. Problem of Estimation subdivided into
Point Estimation: Gives a point value for the random variable parameter.
Interval Estimation: Gives the range of value or interval in which random variable parameter falls in with a given probability.
2. Test of Hypothesis

In this article we are concerned about just highlights of what Inferential Statistics. To know more about in detail, tune into my other articles.

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Problem Solver, Data Science, Actuarial Science, Knowledge Sharer, Hardcore Googler