The Pearson correlation coefficient, sometimes known as Pearson’s r, is a statistic that determines how closely two variables are related. Its value ranges from -1 to +1, with 0 denoting no linear correlation, -1 denoting a perfect negative linear correlation,…

## Chi-Square test using R

A chi-square test is used to analyze nominal (sometimes known as categorical) data. It is pronounced kai and is frequently written as a χ2 test. It’s used to compare the observed frequencies in each sample’s response categories. The null hypothesis…

## Random Forest in R

Random Forest is a strong ensemble learning method that may be used to solve a wide range of prediction problems, including classification and regression. Because the method is based on an ensemble of decision trees, it offers all of the…

## Paired sample t-test using R

The paired sample t-test, sometimes called the dependent sample t-test, is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. In a paired sample t-test, each subject or entity is measured twice, resulting…

## One-Way ANOVA using R

The one-way analysis of variance (ANOVA) is used to determine whether there are any statistically significant differences between the means of three or more independent (unrelated) groups. This guide will provide a brief introduction to the one-way ANOVA, including the…

## Principal Component Analysis (PCA) using R

PCA means Principal Component Analysis. PCA is a multivariate technique that is used to reduce the dimension of a data set. More precisely, PCA is concerned with explaining the variance-covariance structure through a few linear combinations of the original variables.…

## Multicollinearity: Why occur and how to remove

What is multicollinearity? Multicollinearity is a statistical situation that occurs in a regression model when two or more predictors or explanatory or independent variables are highly correlated to each other. In this situation, there exists a strong correlation among the…

## Independent Component Analysis (ICA) using R

ICA means Independent Component Analysis. ICA is the most powerful and widely used statistical technique which is used to separate independent sources from their mixture. It is also known as blind source separation technique. The Situation where we use ICA…