[TBD]Understanding Parametric statistics in data science

Introduction

Laymen explanation

If underline probability distribution(PDF) can be found, then use parametric statistics for ML modelling. If you like to know why, then this document helps.

Technical explanation

Parametric statistics is a branch of statistics which assumes that sample data comes from a population that can be adequately modeled by a probability distribution that has a fixed set of parameters

Advantage of parametric statistics

• Its performance is better than non-parametric model

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Parametric model vs parametric statistics

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A Parametric Model is a concept used in statistics to describe a model in which all its information is represented within its parameters. In short, the only information needed to predict future or unknown values from the current value is the parameters.

Point to remember

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Reference

https://www.isical.ac.in/~caiml/courses/workshop002/

https://en.wikipedia.org/wiki/Parametric_statistics

https://en.wikipedia.org/wiki/Parametric_model

https://deepai.org/machine-learning-glossary-and-terms/parametric-model