Introduction

It is the root of data analysis, and it involves the analyzing data to help define and regulate business needs. Companies have lots of data and accurately analyzing it and leads to increased productivity and probability.

It provides an approach oriented towards engineering as well as chemical and physical sciences. 

Statistics is a branch of mathematics which deals with the interpretation of the data. It works in the wide variety of the feilds as in the private as well as public sectors. 

Applied statistics is about using statistics for solving other problems. 

Whereas probability deals with the concept of study of machine learning and data science. It is an branch of science which has the outgrowth of the theory of probability. 

Need: 

• To solve pratical problems in today’s data centric era.
• Determines what kind of data has to be collected.
• Tells how to collect the data.
• Analyzing the data using statistical tools.
• Alogrithms and software also plays an important role in this.

Advantages:

• Probability and statistics are closely linked because statistical data are frequently analyzed to see whether conclusions can be drawn rightfully about a particular paradox and also to make forecast about future events.
• Helps in making difference between reasonable and doblous conclusions.
• Tends to produce accurate results.
• It helps in providing better understanding .
• It helps in providing the description of nature’s paradox.
• It helps in proper and efficient planning of statistics in any feild of study.
• It helps in collecting accurate quantitave  data.

Conclusion:

It helps in maintaining appropriate data. It provides better undersyanding skills. Produces accuraate results. It helps in solving pratical issues according to today’s centric word It is the root of data analysis, which helps in regulating business needs.