Provides tutorials  alongside practical examples in R. Topics include statistical simulations, data visualization, and common challenges in scientific analysis. The content is designed to offer useful insights for those working with data, without unnecessary complexity.

Here are some of the most interesting R packages I’ve discovered among the 2025 releases. These are especially useful for demographic statistics, teaching, and time series correlation analysis.

Interesting New R Packages (2025)

Giorgio Luciano

Anscombe’s Quartet, known as the “Anscombe’s Test,” consists of four datasets with very similar descriptive statistics but visually distinct characteristics. These quartets serve as an enlightening example of the importance of visualizing data before drawing conclusions. In this post, we will delve into how to calculate and visualize Anscombe’s Quartet using R and the powerful ggplot2 library.

Anscombe’s Quartet

The Birthday Paradox is a probabilistic problem concerning the likelihood that two people in a group share the same birthday. At first glance, it might seem like the probability is very low, but in reality, it’s higher than you might think. The paradox is based on the fact that there are many possible combinations of people’s birthdays within a group.

The Birthday Paradox: When Probability Plays Tricks

Non-Negotiables for Your Data
 

In today’s data-driven world, it is essential to understand the difference between a spreadsheet and a database, as well as the importance of proper data management. This post will explain why Excel should not be used as a database and provide key guidelines for effectively managing and analyzing data.

Non-Negotiables for Your Data

library(viridis)  # Import the viridis color palette library library(ggplot2) set.seed(123)  # Set a seed for reproducibility num_flips &lt;- 50000 flips &lt;- sample(c("Heads", "Tails"), num_flips, replace = TRUE) # Image aspect ratio aspect_ratio &lt;- 1  # You can customize the aspect ratio here n_col &lt;- round(sqrt(num_flips) * aspect_ratio) n_row &lt;- ceiling(num_flips / n_col) # Create a color matrix to represent coin flips colors &lt;-

Namespaces in shiny: Why you need them

Dice rolling is a pastime enjoyed by many, whether in board games or games of chance. But have you ever wondered how the sum of multiple dice rolls behaves when you roll them repeatedly? In this blog post, we embark on a journey into the world of dice rolls and the fascinating Central Limit Theorem. We’ll uncover how the sum of dice rolls can transform into a Gaussian distribution as the number of rolls increases.

Central Limit Theorem with Dice Rolls

Creating an RSS feed for your Quarto blog can be tricky, but there’s one essential detail that can save you a lot of frustration: matching your file names correctly. The Key to Success: Matching Names   When configuring your RSS feed in the _quarto.yml file, ensure that the name you use for the RSS icon matches the name of your listing file. This might seem minor, but it’s crucial for your RSS feed to work properly.

Configuring Your RSS Feed in Quarto: A Crucial Naming Tip

As scientists and data analysts, we often encounter complex curves in our work. These could be spectroscopic data, chromatograms, or any other type of signal that appears as a single peak but might be composed of multiple underlying components. The process of breaking down such a curve into its constituent parts is known as curve deconvolution or peak fitting.

The Pitfall of Arbitrary Curve Deconvolution: A Cautionary Tale for Scientists and Students

Excel non è un Database: Linee Guida Essenziali per una Corretta Gestione dei Dati
 

È fondamentale comprendere la differenza tra un foglio di calcolo e un database, nonché l’importanza di una corretta gestione dei dati. Di seguito sono riportati motivi per cui Excel non dovrebbe essere utilizzato come database, insieme a criteri essenziali per gestire e analizzare i dati in modo efficace.

Criteri Essenziali per La Gestione Dati

Confronto tra Excel e Database nella Gestione Clinica dei Dati: Errori e Sicurezza


 Caso Excel: Errore nel Valore di una Glicemia

Un errore comune in Excel è l’inserimento di valori non corretti a causa di formati non standardizzati. Supponiamo di avere una tabella in cui si registrano i valori di glicemia dei pazienti.

Confronto tra Excel e Database nella Gestione Clinica dei Dati: Errori E Sicurezza

Formattazione Condizionale

La

 formattazione condizionale

in Excel consente di applicare automaticamente stili di formattazione (come colori delle celle, stili di carattere o bordi) alle celle in base a determinate condizioni o criteri specifici.

Formattazione condizionale in Excel

Have you ever wondered why casinos seem to have a mysterious edge, making them consistently profitable? Let’s explore a paradox in the world of gambling, where the number zero takes center stage and helps the house always come out on top. To illustrate this phenomenon, let’s simulate the game of roulette using the R programming language. We’ll focus on a simple bet: predicting whether the ball will land on red or black.

The Illusion of Luck: How the Number Zero Always Wins in the Casino

Today, we embark on a visual exploration of card shuffling, delving into a captivating technique known as the Faro shuffle. Unlike conventional shuffling, the Faro shuffle promises not just randomness but a mathematical symphony that unfolds card by card, a dance that echoes with the precision of numbers.  In the quest to unravel the intricacies of card shuffling, we turn to the Faro shuffle, a technique that mimics the graceful dance of cards.

Exploring Card Shuffling: A Visual Journey

List of packages I’ve found useful in my workflow during 2022 (in no particular order) Plot

 ggvoronoi: Voronoi Diagrams and Heatmaps with ‘ggplot2’


 tags

: #ggplot #tidyverse #voronoi [cran package link] https://CRAN.R-project.org/package=ggvoronoi

 description from the author/vignette


 ggh4x: Hacks for ‘ggplot2’


 tags

: #ggplot #tidyverse [cran package link]

R Packages 2022 list

List of packages I’ve found useful in my workflow during 2024 (so far) Plot

 spiralize: Visualize Data on Spirals


 tags

: #plot [cran package link] https://CRAN.R-project.org/package=spiralize

 description from the author/vignette


 panelView: Visualizing Panel Data


 tags

: #plot [cran package link] https://CRAN.R-project.org/package=panelView

 description from the

R Packages 2024 list so far

Pizza, a beloved culinary delight, comes in various sizes. To better understand the implications of pizza size on the amount of pizza consumed, we establish a new standard unit called the

 standard pizza radius

, denoted by the letter , which measures 6 inches. This article examines how the area of a pizza changes with size and demonstrates that one extra-large pizza can provide more pizza than two standard-sized pizzas.

A Mathematical Exploration of Pizza Sizes

In this blog post, we will dive into the fascinating world of coin flip sequences. Leveraging the capabilities of R, we will conduct simulations to gain insights into the probabilities of consecutive sequences of heads or tails. Let’s kick things off by simulating coin flips using R. We’ll conduct experiments with varying numbers of flips to observe how the results evolve.

Exploring Coin Flip Sequences with Simulation in R

The Monty Hall problem is a famous probability puzzle. In this scenario, a contestant on a game show is presented with three doors. Behind one door, there is a car, while behind the other two, there are goats. The contestant chooses one door, and then the host, Monty Hall, who knows what is behind each door, opens one of the remaining two doors to reveal a goat.

Monty Hall simulation

Introduction to Exploratory Data Analysis (EDA)
 

Exploratory Data Analysis (EDA) is the crucial first step in the data analysis process. Before applying complex statistical models or machine learning algorithms, it is essential to understand the structure, trends, and peculiarities of the data you are working with.

Data Visualization

Embark on a journey into the realm of Dungeons &amp; Dragons as we unravel a captivating fiddle riddle involving a dice duel. Using the power of the R programming language and the Monte Carlo simulation method, we’ll simulate the outcomes of duels between two players, each armed with a bag containing six distinct DnD dice. Prepare to explore the fascinating world of probability and randomness!

Unraveling the DnD Dice Duel Riddle with Monte Carlo Simulation in R

In this blog post, we’ll delve into the realm of casino roulette and use R simulations to estimate the frequency of the number 0 appearing over the span of a year (40 spins per hour x 24 hours x 365 days) . Roulette, a classic casino game, is known for its unpredictability, making it an interesting subject for probability exploration.

Data & Molecule Bits

R Packages 2022 list