-
Why is Central Tendency Important? Why Do We Use It?
Central tendency is one of the basic tools to help us understand essential information about the values of a dataset.
-
Creating Tables for Descriptive Analysis
EDA
When conduction EDA, multiple steps are required. When using python, other tools can be used to facilitate visualizations and other commands.
-
The Future of Biological Data Analysis
A deep-learning framework reveals whole-body perturbations at cell level, 2026
Machine Learning (ML) is often associated with predictions. And that is the case most of the time. However, its use expand beyond predictions. A new paper published in Nature caught my attention.
-
Simple vs. Stratified Sampling What's the Difference?
In research, the best data you can feed a model is the whole population. After a decade of working with data, working with the entire population is almost never the case. For most of the analyses we create, we end up working with a sample.
-
The Statistical Trick That Lets 1,000 People Represent Millions
Growing up, watching the first presidential elections after the military dictatorship in Brazil caught my attention. I watched a very young governor take the lead in the general elections
-
Central Limit Theorem
The central limit theorem (CLT) is, arguably, the most important theorem in statistics. It is, in many cases, an introductory statistics course.
-
All Models Are Wrong!
”All models are wrong, but some are useful.” Charles Box
-
What Universal Optmization Works Best? No-Free-Lunch Theorem
There are hundreds, if not thousands, of algorithms and statistical methods. When I first started in this field, the first method I tried in every single dataset was K-means. It was my go-to algorithm.
-
Unweighted and Weighted Logistic Regression Models
Even after so many years, I still remember one of my very first logistic regression projects. I was so proud of it. Until my supervisor kicked it back and told me that I had to weigh it.
-
The AI Bubble Nobody Wants to Talk About
There isn't one day when I open the news or social media that I don't come across AI news.
About
I am a veteran. I spent years in intelligence analysis, where being confidently wrong carried a cost, and that is where I learned to separate what evidence shows from what it suggests. I have a master's in journalism and communications, and I am finishing a doctorate in data science on how findings get communicated. I work in English and Portuguese.