- Overview of data distributions - Jun 10, 2020.
With so many types of data distributions to consider in data science, how do you choose the right one to model your data? This guide will overview the most important distributions you should be familiar with in your work.
- Looking Normal(ly Distributed) - May 20, 2020.
This article investigates when some probability distributions look normal "enough" for a statistical test.
- Probability Distributions in Data Science - Feb 26, 2020.
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
- 5 Probability Distributions Every Data Scientist Should Know - Jul 4, 2019.
Having an understanding of probability distributions should be a priority for data scientists. Make sure you know what you should by reviewing this post on the subject.
- Basic Statistics in Python: Probability - Aug 21, 2018.
At the most basic level, probability seeks to answer the question, "What is the chance of an event happening?" To calculate the chance of an event happening, we also need to consider all the other events that can occur.
- What is Normal? - Jul 31, 2018.
I saw an article recently that referred to the normal curve as the data scientist's best friend. We examine myths around the normal curve, including - is most data normally distributed?
- Explaining the 68-95-99.7 rule for a Normal Distribution - Jul 19, 2018.
This post explains how those numbers were derived in the hope that they can be more interpretable for your future endeavors.