Essential Statistics for Data Science

Learn basic statistical concepts used in data science and machine learning

Benjamin Obi Tayo Ph.D.

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About the Author

Benjamin O. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com

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INTRODUCTION

Statistical concepts are used widely to extract useful information from data. This article will review essential statistical concepts applicable in data science and machine learning.

Probability Distribution

A probability distribution shows how feature values are distributed around the mean value. Using the iris dataset, the probability distributions for the sepal length, sepal width, petal length, and petal width can be generated using the code below.

import numpy as np

import matplotlib.pyplot as plt

from sklearn import datasets

import seaborn as sns

iris = sns.load_dataset("iris")

sns.kdeplot(data=iris)

plt.show()
Probability distribution of sepal length, sepal width, sepal width, petal length, and petal width | Image by Author.

Mode

Lets now focus on the sepal length variable. The probability distribution of the sepal length variable is shown below.

Probability distribution of sepal length variable | Image by Author

We observe that the probability distribution of the sepal length variable has a single maximum, hence it is unimodal. The value of the sepal length where the maximum occurs is the mode, which is about 5.8.

A plot of the probability distribution of the petal width variable is shown below.

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Benjamin Obi Tayo Ph.D.

Dr. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com