T-tests shine when there are two groups. Add a third and you’re tilting at windmills… each pairwise test inflates your error, turning “maybe” into “must be.” ANOVA reframes the question: is between-group variation meaningfully larger than within-group noise? One gatekeeping test protects your alpha, then (if warranted) planned contrasts or honest post-hocs tell you where […]
One Test, Many Means: Why ANOVA Exists Read More »
A confidence interval isn’t “the range where the truth lives.” It’s a contract: repeat this method forever, and this style of interval would catch the truth at your chosen rate. That’s it. Want tighter bounds? Pay with more data or more discipline; don’t pay with wishful thinking. Before you compute anything, ask: what margin would
Confidence Intervals: Promises About Process, Not Fortune-Telling Read More »
If you don’t name the null, your brain will. And it’s a generous storyteller. The null isn’t cynicism; it’s the control that keeps you from worshiping coincidence. “No difference. No association. No effect.” Boring? Good. That’s the point. Only when your data make that stance unlikely do you earn a new sentence. Begin by writing
Start With the Null… or You’ll Start With a Story Read More »
