Summary In today's episode, I explore whether one variable can cause another without showing a statistical correlation, breaking down five real-world scenarios where this hidden causation happens. Here's what this means for you. You gain a sharper eye for catching causation buried in messy, hidden, or canceling data so you stop trusting correlation alone. You'll…
Summary In today's episode, I explore why merging liberal arts with science creates a uniquely valuable skill set and answer Mbeza's question about combining creative and technical disciplines. Here's what this means for you. You gain a framework for building versatile expertise that artificial intelligence struggles to replicate. You'll also learn these concepts: why you…
Summary In today's episode, I walk through how to determine whether your A/B test results are truly meaningful or simply random chance. Here's what this means for you. You gain a clear two-step framework for validating any test before making business decisions on it. You'll also learn these concepts: how a proportion test reveals whether…
Summary In today's episode, I walk through exploring a brand-new COVID-19 behavioral dataset from Imperial College London and YouGov covering 29 countries. Here's what this means for you. You gain a repeatable workflow for opening an unfamiliar dataset and pulling out early insights without getting overwhelmed. You'll also learn these concepts: why the codebook is…
Summary In today's episode, I break down how the scientific method applies to data science and why the problem definition phase matters far more than most people realize. Here's what this means for you. You'll learn why rushing past exploration and straight to a hypothesis almost always leads to flawed experiments and wasted effort. You'll…
Summary In today's episode, I walk through how to analyze FBI hate crime data and uncover the massive underreporting problem affecting the LGBTQIA community. Here's what this means for you. You gain practical techniques for turning messy public datasets into actionable insights that can drive real social change. You'll also learn these concepts: how inconsistent…
Summary In today's episode, I walk through how to decide which variables matter most when analyzing marketing data, covering everything from regression basics to spotting spurious correlations. Here's what this means for you. You gain a practical framework for separating meaningful business signals from statistical noise that could send your decisions in the wrong direction.…
Summary In today's episode, I walk through turning the public Open Food Facts nutrition database into advanced, original content marketing using R. Here's what this means for you. You gain a repeatable method for transforming any open dataset into unique, opinion-driven content by cleaning, scaling, and weighting the fields to match your editorial point of…
Jessica asks, “When it comes to marketing data science, I’ve got very good business knowledge, but lack of the technical side. any advice?” The first question you have to ask is whether you need the hands-on skills or just knowledge of what’s possible. The second question is what skills you already have. Remember that in…
Summary In today's episode, I walk through how to build technical and statistical skills for marketing data science even when you start with strong business knowledge. Here's what this means for you. You'll discover that learning the math first, then the tools, prevents wasted effort and helps you make smarter technology choices. You'll also learn…
