Statistics in ML

Every Machine Learning enthusiast have to face this sweet concept during the journey. I am also facing it and now if i have got to know something i will share this one.
So let's get started.
How statistics can be defined?. Statistics is a collection, organisation, analysis and interpretation of data which includes..

1)Design of experiments

2)Sampling

3)Descriptive Analysis

4)Inferential Statistics

5)Probability Theory

Now there are two types of Statistics...
Descriptive Statistics
Inferential Statistics
in few words we have to explain then it would be like

Descriptive Statistics

It collects data, organize the data, characterize present data also.

Inferential Statistics
It make inferences , then do the hypothesis testing also determine the relationships and then make the predictions.

Now let's understand Descriptive Statistics in little bit deep manner. These are the methods for organizing and summarizing the data.

For example, Table and Graphs are used to organize the data and descriptive values such as the average score are used to summarize the data.

A descriptive value for a population is called a Parameter and descriptive value for a sample is called Statistic.

After this we should know the classification of variables or the level of data analysis you can say.
You can use the image for understanding.