Statistics

modeling is the top of analytics value. It doesn’t give attention to what happened, and even what occur – it takes analytics further by telling us what we should always do to vary...

You will discover the complete code for this instance at the underside of this post. odds model for ordinal logistic regression was first introduced by McCullagh (1980). This model extends binary logistic regression to situations...

: 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...

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...

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...

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...

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...

-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...