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Z- Statistics, T-Statistics, P-Statistics are Still Confusing you?
Author(s): Amit Chauhan Definitions and concepts in Statistics for machine learning Continue reading on Towards AI » Published via Towards AI …
Linear Regression and Type I Error
Author(s): George Pipis An example of Type I Error in Multivariate Linear Regression Continue reading on Towards AI » Published via Towards AI …
Odds Ratio Does What Risk Ratio Fails to Do — an Intuitive Example
Author(s): Atul Sharma Statistics Odds Ratio Does What Risk Ratio Fails to Do — an Intuitive Example Understand the concept from scratch Photo by Sydney Sims on Unsplash Let’s begin by dropping the ultimate takeaway of this blog: “The odds ratio is a consistent measure for both …
The Confusion Behind Logistic Regression
Author(s): Charanraj Shetty Understanding the Math Intuition Continue reading on Towards AI » Published via Towards AI …
Concepts of Bias and Variance In Dataset
Author(s): Amit Chauhan Basic understanding of definitions used in data science Continue reading on Towards AI » Published via Towards AI …
Linear Regression
Author(s): Charanraj Shetty OLS and Gradient Descent Continue reading on Towards AI » Published via Towards AI …
Central Tendency: Demystifying “Average” Term
Author(s): Luthfi Ramadhan Statistics How people use the “Average” term to deceive others Photo By: Freepik on Pinterest What is Central Tendency? Central Tendency is a number that describes the middle or typical value of a data. It helps you derive valuable information …
Descriptive Statistics with Pandas
Author(s): Sujan Shirol Statistical concepts with examples, formula, and python code Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Bayesian Inference: Beyond Estimating Statistical Models
Author(s): ___ Why and how to apply Bayesian inference to build causal models Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Naive Bayes Classification
Author(s): Charanraj Shetty Probability basics and Bayes theorem Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Exploring Descriptive Statistics Using Pandas and Seaborn
Author(s): Indhumathy Chelliah Quantitative approach and Visual approach Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Simple Linear Regression Tutorial for Machine Learning (ML)
Author(s): Pratik Shukla, Roberto Iriondo Source: Image by the Author. Diving into calculating a simple linear regression and linear best fit with code examples in Python and math in detail This tutorial’s code is available on Github and its full implementation as …
Bernoulli Distribution — Probability Tutorial with Python
Author(s): Pratik Shukla, Roberto Iriondo Source: Unsplash Probability, Statistics Bernoulli distribution tutorial — diving into the discrete probability distribution of a random variable with examples in Python In this series of tutorials, we will dive into probability distributions in detail. We will not just showcase …
Moment Generating Function Tutorial
Source: Pexels Diving into the Moment Generation Function for probability distribution with a complete derivation and code examples in Python Author(s): Pratik Shukla, Roberto Iriondo This tutorial’s code is available on Github and its full implementation as well on Google Colab. Table of …
Stock Price Change Forecasting with Time Series: SARIMAX
Author(s): Avishek Nag Machine Learning, Statistics High-level understanding of Time Series, stationarity, seasonality, forecasting, and modeling with SARIMAX Time series modeling is the statistical study of sequential data (may be finite or infinite) dependent on time. Though we say time. But, time here …
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