#datasciencetraining — Public Fediverse posts

At first glance, bar charts might seem like a simple visualization type. But with a little creativity, they can be enhanced in countless ways to reveal deeper insights and make your data shine.

The attached visual highlights a variety of bar chart styles to inspire your work.

Take a look here for more details: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r

#datastructure #data #tidyverse #rstats #package #datasciencetraining

At first glance, bar charts might seem like a simple visualization type. But with a little creativity, they can be enhanced in countless ways to reveal deeper insights and make your data shine.

The attached visual highlights a variety of bar chart styles to inspire your work.

Take a look here for more details: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r

#datastructure #data #tidyverse #rstats #package #datasciencetraining

I used to think that writing sophisticated R code meant using all the advanced features and chaining long functions together...

Fancy code can be fun, but clean code makes collaboration and debugging so much easier.

Stay informed on data science by joining my free newsletter. Check out this link for more details: http://eepurl.com/gH6myT

#datastructure #datasciencecourse #datasciencetraining

I used to think that writing sophisticated R code meant using all the advanced features and chaining long functions together...

Fancy code can be fun, but clean code makes collaboration and debugging so much easier.

Stay informed on data science by joining my free newsletter. Check out this link for more details: http://eepurl.com/gH6myT

#datastructure #datasciencecourse #datasciencetraining

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

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

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

Bayes' theorem, a key concept in probability theory, is crucial for making informed decisions in uncertain situations. It allows us to update our beliefs based on new evidence.

This theorem mathematically describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

The visualization in this post is based on an image from Wikipedia (link: https://en.wikipedia.org/wiki/Bayes%27_theorem#/media/File:Bayes_theorem_visual_proof.svg).

More details: https://statisticsglobe.com/bayes-theorem-explained

#datasciencetraining #Rpackage #Python

Bayes' theorem, a key concept in probability theory, is crucial for making informed decisions in uncertain situations. It allows us to update our beliefs based on new evidence.

This theorem mathematically describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

The visualization in this post is based on an image from Wikipedia (link: https://en.wikipedia.org/wiki/Bayes%27_theorem#/media/File:Bayes_theorem_visual_proof.svg).

More details: https://statisticsglobe.com/bayes-theorem-explained

#datasciencetraining #Rpackage #Python

Hey, I've published a tutorial on how to draw an interactive violin plot using the plotly library in the R programming language. The tutorial was created in collaboration with Ifeanyi Idiaye: https://statisticsglobe.com/plotly-violin-plot-r

#datasciencetraining #statisticians

Hey, I've published a tutorial on how to draw an interactive violin plot using the plotly library in the R programming language. The tutorial was created in collaboration with Ifeanyi Idiaye: https://statisticsglobe.com/plotly-violin-plot-r

#datasciencetraining #statisticians

Hey, I've published a tutorial on how to visualize the results of a Principal Component Analysis (PCA) using the Python programming language. The tutorial was created in collaboration with Paula Villasante Soriano & Cansu Kebabci: https://statisticsglobe.com/visualization-pca-python

#pythonforbeginners #datasciencetraining

Hey, I've published a tutorial on how to visualize the results of a Principal Component Analysis (PCA) using the Python programming language. The tutorial was created in collaboration with Paula Villasante Soriano & Cansu Kebabci: https://statisticsglobe.com/visualization-pca-python

#pythonforbeginners #datasciencetraining

Hey, I've created a tutorial on how to calculate the mean by group of a pandas DataFrame in the Python programming language: https://statisticsglobe.com/calculate-mean-group-python

#Statistics #datasciencetraining #pythonforbeginners

Hey, I've created a tutorial on how to calculate the mean by group of a pandas DataFrame in the Python programming language: https://statisticsglobe.com/calculate-mean-group-python

#Statistics #datasciencetraining #pythonforbeginners

Hey, I've created a tutorial on how to calculate multiple summary statistics using the R programming language. The tutorial shows examples for Base R & the dplyr package: https://statisticsglobe.com/calculate-multiple-summary-statistics-r

#datasciencetraining #statisticians #Package #tidyverse

Hey, I've created a tutorial on how to calculate multiple summary statistics using the R programming language. The tutorial shows examples for Base R & the dplyr package: https://statisticsglobe.com/calculate-multiple-summary-statistics-r

#datasciencetraining #statisticians #Package #tidyverse

Hey, I've published a tutorial on how to draw interactive time series plots using the plotly package in the Python programming language. The tutorial was created in collaboration with Ifeanyi Idiaye: https://statisticsglobe.com/time-series-plotly-graph-python

#statisticians #datasciencetraining #datavisualization

Hey, I've created a tutorial on how to calculate the standard deviation using the Python programming language: https://statisticsglobe.com/standard-deviation-python

#datasciencetraining #pythonprogramminglanguage

Hey, I've created a tutorial on how to calculate the standard deviation using the Python programming language: https://statisticsglobe.com/standard-deviation-python

#datasciencetraining #pythonprogramminglanguage