Statistics

Statistics

Ridge Regression as MAP Estimation – Supporting notes

This is one of the most beautiful connections in machine learning – let me break down exactly why Ridge regression is MAP estimation in...

Statistics

Maximum A Posteriori (MAP) Estimation – Clearly Explained

Maximum A Posteriori (MAP) estimation is a Bayesian method for finding the most likely parameter values given observed data and prior knowledge. Unlike maximum...

Statistics

F Statistic Formula – Explained

The F statistic is used in statistical hypothesis testing to determine if there are significant differences between group means. It is most commonly used...

Statistics

Correlation – Connecting the Dots, the Role of Correlation in Data Analysis

Correlation is a fundamental concept in statistics and data science. It quantifies the degree to which two variables are related. But what does this...

Statistics

Hypothesis Testing – A Deep Dive into Hypothesis Testing, The Backbone of Statistical Inference

Explore the intricacies of hypothesis testing, a cornerstone of statistical analysis. Dive into methods, interpretations, and applications for making data-driven decisions. In this Blog...

Statistics

Sampling and Sampling Distributions – A Comprehensive Guide on Sampling and Sampling Distributions

Explore the fundamentals of sampling and sampling distributions in statistics. Dive deep into various sampling methods, from simple random to stratified, and uncover the...

Statistics

Law of Large Numbers – A Deep Dive into the World of Statistics

The Law of Large Numbers (LLN) is a fundamental theorem in probability and statistics, serving as the basis for many concepts and practices in...

Statistics

Central Limit Theorem – A Deep Dive into Central Limit Theorem and its Significance in Statistics

Statistics offers a vast array of principles and theorems that are foundational to how we understand data. Among them, the Central Limit Theorem (CLT)...

Statistics

Skewness and Kurtosis – Peaks and Tails, Understanding Data Through Skewness and Kurtosis”

Statistics has a variety of tools to help us understand and interpret data. Two such tools are skewness and kurtosis, which give us insights...

Statistics

Measures of Dispersion – Unlocking the Variability Diving Deep into Measures of Dispersion

Dive deep into the world of statistics and measures of dispersion, from understanding its essence to its practical application using Python. In this Blog...

Statistics

Quantiles and Percentiles – Understanding Quantiles and Percentiles, A Deep Dive with Python Examples

Quantiles and percentiles are crucial statistical concepts that assist in understanding and interpreting data. They are essentially tools to help divide datasets into smaller...

Statistics

Measures of Central Tendency – A Clear Guide with Examples on Measures of Central Tendency

When diving into the world of statistics, you’ll frequently come across the term “measures of central tendency”. But what exactly does it mean, and...

Statistics

Types of Data in Statistics – A Comprehensive Guide

Statistics is a domain that revolves around the collection, analysis, interpretation, presentation, and organization of data. To appropriately utilize statistical methods and produce meaningful...

Statistics

Descriptive and Inferential Statistics – Deep Dive into Descriptive and Inferential Statistics

In statistics understanding the difference between descriptive and inferential statistics is crucial for anyone looking to make sense of data, whether it’s for academic...

Statistics

R Squared Interpretation

Statistics

Partial Correlation

What is Partial Correlation and it’s purpose Partial correlation is used to find the correlation between two variables (typically a dependent and an independent...

Statistics

Chi-Square test – How to test statistical significance for categorical data?

What is chi-square test and its purpose? Chi-square test was invented in the year ‘1900’ by the revered mathematician ‘Karl Pearson’. Chi-square test, also...

Statistics

Brier Score – How to measure accuracy of probablistic predictions

Brier score is an evaluation metric that is used to check the goodness of a predicted probability score. This is very similar to the...

Statistics

One Sample T Test – Clearly Explained with Examples | ML+

One sample T-Test tests if the given sample of observations could have been generated from a population with a specified mean. If it is...