# Inferential Statistics Articles

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Anmolika Singh
Updated on August 08, 2024

## Guide to Power Analysis and Statistical Power

Power analysis is a process that involves evaluating a test’s statistical power to determine the necessary sample size for a hypothesis test. Learn more.

Richard Farnworth
Updated on August 01, 2024

The birthday paradox is the probability theory that the probability of two people sharing the same birthday grows with the number of possible pairings.

Updated on June 26, 2024

## The Kruskal Wallis Test: A Guide

The Kruskal-Wallis test is an important statistical analysis for data that doesn’t follow normal distributions. Our expert shows you how it works here.

Jeremy Zhang
Updated on January 17, 2024

## Importance Sampling Explained

Importance sampling is an approximation method that uses a mathematical transformation to take the average of all samples to estimate an expectation. Here’s how to do it.

Terence Shin
Updated on December 21, 2023

## Statistical Bias: 6 Types of Bias in Statistics

Statistical bias is when a model or statistic is unrepresentative of the population. There are six main types of bias in statistics.

Anthony Corbo
Updated on November 07, 2023

## What Is Inferential Statistics?

Inferential statistics is the practice of using sampled data to draw conclusions or make predictions about a larger sample data sample or population.

Jørgen Veisdal
Updated on October 09, 2023

## The Pigeonhole Principle Explained

The pigeonhole principle states that if n items are put into m containers, with n > m, then at least one container must contain more than one item.

Niklas Donges
Updated on March 15, 2023

## Intro to Descriptive Statistics for Machine Learning

What you need to know to get started with descriptive statistical analysis.

Sara A. Metwalli
Updated on March 15, 2023

## 4 Probability Distributions Every Data Scientist Needs to Know

If you’re just getting started on your journey toward becoming a data scientist, these are the 4 most common distributions you’ll encounter.