# Search results for ‘parameters’

## When Testing Parameters Might Make Sense

This example is derived from ongoing conversations with a colleague, and portions of this post (mathematified) might show up in a paper. The genesis of this example is from Ron Christensen’s 2005 […]

## Observable-Based , Predictive, or Causal Statistics? Don’t Test! Don’t Estimate!

The term predictive statistics is used to describe a focus on observables, and not on any invisible model-based parameters as is found in estimation and null hypothesis significance testing. It isn’t sticking, […]

## The Danish Mask Study Shows Masks Aren’t Worth It

HUFFIN’, PUFFIN’ & BLUFFIN’ The blustery squid-stained panicked hersteric Nassim Nicholas Taleb—the man who called those who dared not run around screeching like teenage girls as he did at the start of […]

## Parameters Aren’t What You Think

I was asked to comment on a post by Dan Simpson exploring the Bernstein-von Mises theorem. This post fits in with the Data Science class, a happy coincidence, and has been so […]

## How To Do Predictive Statistics: Part VIII — Starting Stan

Review! You must at least review the first lessons—all class material is on one page for ease. I’ll have more words about the mysticism of simulation, but I’ve said it all before […]

## Control Groups With No Cancers In Hormesis Data Sets

A well known paper by Duport et al. on radiation hormesis makes a statement about control groups which is not quite right. The paper is “Database of Radiogenic Cancer in Experimental Animals […]

## How To Do Predictive Statistics: Part IX Stan — Logistic & Beta Regression

Review! We’re doing logistic and beta regression this time. These aren’t far apart, because the observable for both lives between 0 and 1; for logistic it is 0 or 1; for beta, […]

## How To Do Predictive Statistics: Part I New (Free) Software Introduction

Introduction Here’s what we always want, but never get, using the old ways of doing statistics: The probability that some proposition Y is true given certain assumptions. Like this:      (1) Pr(Y […]