Statistical Methods & Thinking

In this episode, we introduce the core ideas behind analyzing time-to-event data—situations where the outcome isn’t just “what happened,” but when it happened.

A key challenge is that some participants haven’t experienced the event yet by the end o... more

In this episode, we step into multivariate thinking and ask a practical question: when do data points naturally form “groups,” and how can we use those groups to make decisions?

We walk through how grouping methods decide what’s “close” or “similar,”... more

This episode is about what to do when your data has many variables at once. We start with the basic idea of how variables “move together” (correlation and covariance), and why that matters for understanding patterns in real datasets.

Then we introdu... more

This episode is about working with categorical outcomes—questions where results fall into categories rather than a numeric scale.

We learn how to check whether two variables are related, how to model the chance of a “yes/no” outcome using multiple ... more

In this episode, we start with Fisher’s “Lady Tasting Tea”—a classic reminder that good questions need good experimental design. Then we shift from continuous outcomes to categorical data: how a simple 2×2 table turns test results into sensitivity/sp... more

This episode moves from one-way ANOVA to two-factor randomized experiments, focusing on how to test main effects and, more importantly, interactions—when the effect of one factor depends on the level of the other.

Using examples like printer sales ... more

This episode introduces the core logic of experimental design and ANOVA: what we mean by causality, factors, and confounders—and why randomization, replication, and blocking are the practical tools that make comparisons fair.

We build the one-way A... more

Episode 6 is about making multiple regression work in real life: how to choose predictors without overfitting, when to transform variables to fix messy variance or nonlinearity, and what to do when predictors are strongly correlated.

We’ll walk thr... more