Importance of Degrees of Freedom In Machine Learning and Statistics.

INTRODUCTION

Degrees of freedom is an important concept from statistics and Data Science(like Machine Learning).

It is often employed to summarize the number of values used in the calculation of a statistic, such as a sample statistic or in a statistical hypothesis test.

In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary.

In short, It represent the number of points of control of a system, model, or calculation.

Each independent parameter that can change is a separate dimension in a d-dimensional space that defines the scope of values that may influence the system, where the specific observed or specified values are a single point in that space.

Mathematically, the degrees of freedom is often represented using the Greek letter nu, which looks like a lower-case “v”.

It may also be abbreviated as “d.f” or simply “df”.

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