Statistics

-up to my earlier article: The Dangers of Deceptive Data–Confusing Charts and Misleading Headlines. My first article focused on how will be used to mislead, diving right into a form of knowledge presentation...

distributions are essentially the most commonly used, numerous real-world data unfortunately will not be normal. When faced with extremely skewed data, it’s tempting for us to utilize log transformations to normalize the distribution...

In models, the independent variables have to be not or only barely depending on one another, i.e. that they are usually not correlated. Nevertheless, if such a dependency exists, that is known as...

Introduction Parameter estimation has been for a long time one of the crucial necessary topics in statistics. While frequentist approaches, akin to Maximum Likelihood Estimations, was once the gold standard, the advance of computation...

truth isn't perfect. From scientific measurements to human annotations used to coach deep learning models, ground truth all the time has some amount of errors. ImageNet, arguably essentially the most well-curated image dataset...

all been in that moment, right? Looking at a chart as if it’s some ancient script, wondering how we’re speculated to make sense of all of it. That’s exactly how I felt once...

That is the (and certain last) a part of a Linear Programming series I’ve been writing. With the core concepts covered by the prior articles, this text focuses on goal programming which is...

While some games, like rock-paper-scissors, only work if all payers choose their actions concurrently, other games, like chess or Monopoly, expect the players to take turns one after one other. In Game Theory, the...