More articles in Statistics

Introduction to Linear Model for Optimization

Linear Model for Optimization is concerned with finding a suitable model. One of the goals is to reduce generalization errors.

Understanding hypothesis testing through an end to end case study

Implementation of Gaussian Naive Bayes in Python Sklearn

Gaussian Naive Bayes is the easiest and rapid classification method available. Learn how to implement it in Python with sklearn.

Creating a Simple Z-test Calculator using Streamlit

Let us learn about one of the most popular Hypothesis tests, i.e. Z-test or and create a z-test calculator in python for hypothesis testing

End to End Statistics for Data Science

Learn how statistics for data science can transform raw data into actionable insights for informed decision-making. Read Now!

Maximum Likelihood Estimation

Explore the fundamentals and advanced concepts of Maximum Likelihood Estimation (MLE) including statistical modeling, Kullback-Leibler divergence, and more.

A Complete Guide on Sampling Techniques for Data Science

In this guide, we will share a detailed deep-dive of what is sampling, what are different sampling techniques, and their industry use cases.

Different Type of Correlation Metrics Used by Data Scientists

The correlation is used to measure the relationship between two variables. Here, we will see the different types of correlation metrics.

Everything you need to know about Hypothesis Testing in Machine Learning

Hypothesis testing is done to confirm our observation about the population using sample data, within the desired error level.

Q-Q plot – Ensure Your ML Model is Based on the Right Distribution

Q-Q plot ,AKA Quantile-Quantile plots, plots the quantiles of a sample distribution against quantiles of a theoretical distribution.