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## Chi-Square Test for Correlation Test in Details: Manual and Python Implementation

Correlation tests are very common in statistics and machine learning. In statistics, a correlation test is important to understand the impact of different variables on the population. For example, say we developed…

ANOVA and ANCOVA

## Dissecting 1-Way ANOVA and ANCOVA with Examples in R

ANOVA (Analysis of Variance) is a process to compare the means of more than two groups. It can also be used for comparing the means of two groups. But that’s unnecessary.…

## A Complete Guide to Confidence Interval, t-test, and z-test in R

The confidence interval, t-test, and z-test are very popular and widely used methods in inferential statistics. They are so important because, for any research or data analysis, we can only…

## A Complete Tutorial on Logistic Regression, and Inference in R

One of the most basic, popular, and powerful statistical models is logistic regression. If you are familiar with linear regression, logistic regression is built upon linear regression. It uses the…

## A Complete Overview of the Probability Distributions with Examples, R Implementation

Our end goal is to draw inferences from the population. We first need to learn about probability because it is the underlying base for statistical inferences, predictive models, and machine…

## Detailed Guide to Multiple Linear Regression Model, Assessment, and Inference

Linear regression is one of those old-school statistical modeling approaches that are still popular. With the development of new languages and libraries, it is now in a much-improved version and…

Simple Linear Regression

## Details of Simple Linear Regression, Assessment, and Inference using ANOVA

A linear relationship between two variables is very common. So, a lot of mathematical and statistical models have been developed to use this phenomenon and extract more information about the…

## Introduction to the Descriptive Statistics

Descriptive statistics summarize, show, and analyze the data and make it more understandable. If the dataset is large, it is hard to make any sense from the raw data. Using…

## Univariate and Bivariate Gaussian Distribution: Clear explanation with Visuals

Gaussian distribution is the most important probability distribution in statistics and it is also important in machine learning. Because a lot of natural phenomena such as the height of a…

## A Complete Guide to Confidence Interval and Calculation in Python

Confidence Interval(CI) is essential in statistics and very important for data scientists. In this article, I will explain it thoroughly with necessary formulas and also demonstrate how to calculate it…