This is a brief update to a previous post on how to measure conspiracy beliefs. My point in the previous post was that a study published in Psychological Medicine used weird measures to capture conspiracy beliefs. In a letter to the editor, Sally McManus, Joanna D’Ardenne and Simon Wessely note that the response options provided […]
Category: statistics
Data visualization: a reading list
Here is a collection of books and peer-reviewed articles on data visualization. There is a lot of good material on the philosophy, principles and practices of data visualization. I plan to update the list with additional material in the future (see the current version as a draft). Do reach out if you have any recommendations. […]
Potpourri: Statistics #65
677. How The Economist presidential forecast works 678. GESIS Workshop: Applied Data Visualization 679. Introduction to R – tidyverse 680. Why Is It Called That Way?! – Origin and Meaning of R Package Names 681. PMAP 8921: Data Visualization 682. Visualising Odds Ratio 683. Exeter Q-Step Resources 684. tidymodels workflow with Bayesian optimisation 685. How […]
How not to measure conspiracy beliefs
A new study in Psychological Medicine concludes: “In England there is appreciable endorsement of conspiracy beliefs about coronavirus. Such ideas do not appear confined to the fringes.” The study, titled ‘Coronavirus conspiracy beliefs, mistrust, and compliance with government guidelines in England’, shows that a lot of people believe various conspiracy theories related to the coronavirus. […]
Maskinlæring
Maskinlæring er en betegnelse for en række statistiske procedurer, der har det til fælles, at de anvender algoritmer til at udlede information og viden fra data. Forskellige maskinlæringsteknikker kan kategoriseres efter, hvordan de udleder viden fra data, altså hvordan de “lærer”. Med andre ord kan maskinlæring forstås som algoritmer, der uden at bero på domæne-specifik […]