#datasciencetraining — Public Fediverse posts

Combining Principal Component Analysis (PCA) with k-means Clustering in R can significantly enhance your data analysis by reducing dimensionality and improving clustering performance.

Check out my article created with Cansu Kebabci: https://statisticsglobe.com/pca-before-k-means-clustering-r

I've also created a video: https://www.youtube.com/watch?v=nzhSjOKSGC8

Furthermore, I offer an extensive online course on PCA: https://statisticsglobe.com/online-course-pca-theory-application-r

#datasciencetraining #bigdata #advancedanalytics #datasciencecourse

Heterogeneous Treatment Effects (HTE) are a game-changer in A/B testing that often gets overlooked.

The visualization recently shared by Leihua Ye highlights that some segments of users, like the top and bottom 5%, might show vastly different outcomes.

For regular updates on data science, statistics, Python, and R programming, subscribe to my free email newsletter! Check out this link for more details: http://eepurl.com/gH6myT

#datasciencetraining #dataanalytics #advancedanalytics

Creating publication-ready plots in R is easier than ever with ggpubr. This extension for ggplot2 simplifies the process of generating clean and professional graphics, especially for exploratory data analysis and reporting.

Course link: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r

#dataanalytics #rstats #dataanalytic #datavisualization #package #datasciencetraining #visualanalytics #datastructure #tidyverse #ggplot2