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Aug 26,2025
Making Bayesian Statistics Accessible to Everyone – Edition 8: Noninformative Priors for Location and Scale Parameters
Introduction In this eighth edition of our Bayesian series, we delve into a refined class of noninformative priors, specifically for location and scale parameters. This builds directly upon our previous edition, where we introduced the…
Aug 26,2025
Introduction to Statistical Decision Theory – Edition 10: Minimaxity, Admissibility, and the Geometry of Statistical Decisions
1. Minimax Rules: Example Consider nonrandomized decision rules only. Randomized minimax rules will be discussed later. $\begin{array}{c|cccccc} & d_1 & d_2 & d_3 & d_4 & d_5 & d_6 \ \hline R(\theta_1, d_i) & 17…
Aug 26,2025
Making Bayesian Statistics Accessible to Everyone – Edition 9: Quiz on Bayesian Fundamentals (Part I)
Introduction Welcome to Edition 9 of our Bayesian series: “Making Bayesian Statistics Accessible to Everyone”. This edition is dedicated to reinforcing your understanding through a 20-question quiz, combining true/false and multiple choice formats. The questions…
Aug 26,2025
Introduction to Statistical Decision Theory – Edition 11: A Medical Application
Introduction This edition focuses on a practical application of statistical decision theory in a medical context. We explore how a doctor can apply a randomized decision rule to minimize potential loss when diagnosing a disease…
Aug 26,2025
Introduction to Statistical Decision Theory – Edition 12: Application to Classification Decisions with Finite Hypotheses
Bayesian Classification with Finite Hypotheses In this lesson, we study how to make good classification decisions using Bayesian Decision Theory. The goal is to decide which group or class an observation belongs to, based on…
Aug 26,2025
Making Bayesian Statistics Accessible to Everyone – Edition 10: Quiz on Bayesian Fundamentals (Part II)
Introduction Welcome to the 10th Edition of Making Bayesian Statistics Accessible to Everyone. This edition contains 25 multiple choice and true/false questions that evaluate your understanding of key concepts, computations, interpretations, and applications presented in…
Aug 23,2025
Making Statistical Concepts Accessible – Edition 1: What is a p-value, simply explained by example?
P-value, short for ‘Probability-Value,’ serves as a crucial metric in hypothesis testing, primarily assessing the strength of evidence against the null hypothesis. Let’s delve into an example: Consider a randomized clinical trial focused on the…
Aug 23,2025
Making Statistical Concepts Accessible – Edition 2: Hypothesis Testing by example
In the inaugural segment of ‘Making Statistical Concepts Accessible,’ we delved into the nuanced world of p-values, providing a clear definition underscored by practical examples. For a detailed understanding, follow the link to the first…
Aug 23,2025
Making Statistical Concepts Accessible – Edition 3: Simple Linear Regression by example
Let’s begin with a Simple Linear Model overview before diving into the practical example: Understanding the relationship between the dosage of a drug (independent variable) and its influence on patients’ health outcomes (dependent variable) Simple…
Aug 23,2025
Making Statistical Concepts Accessible – Edition 4: Discerning Variable Types for Informed Analysis
Understanding the scale of a variable is paramount in determining the appropriate statistical analysis. The type of variable you’re working with dictates the methodologies and tools you should employ. In our third serie of making…
