Statistics

The Role of Luck in Sports: Can We Measure It?

: When Skill Isn’t Enough You’re watching your team dominate possession, double the variety of shots… and still lose. Is it just bad luck? Fans blame referees. Players blame “off days.” Coaches mention “momentum.” But what...

Data Drift Is Not the Actual Problem: Your Monitoring Strategy Is

is an approach to accuracy that devours data, learns patterns, and predicts. Nonetheless, with the perfect models, even those predictions could crumble in the true world with no sound. Firms using machine learning...

Estimating Product-Level Price Elasticities Using Hierarchical Bayesian

In this text, I'll introduce you to hierarchical Bayesian (HB) modelling, a versatile approach to mechanically mix the outcomes of multiple sub-models. This method enables estimation of individual-level effects by optimally combining information across...

What Statistics Can Tell Us About NBA Coaches

as an NBA coach? How long does a typical coach last? And does their coaching background play any part in predicting success? This evaluation was inspired by several key theories. First, there was a...

Learn the Math Needed for Machine Learning

generally is a scary topic for people. A lot of you must work in machine learning, however the maths skills needed could seem overwhelming. I'm here to inform you that it’s nowhere as intimidating as...

The Dangers of Deceptive Data Part 2–Base Proportions and Bad 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...

Log Link vs Log Transformation in R — The Difference that Misleads Your Entire Data Evaluation

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...

When Predictors Collide: Mastering VIF in Multicollinear Regression

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...

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