866. Which color scale to use when visualizing data 867. When to use quantitative and when to use qualitative color scales 868. When to use sequential and when to use diverging color scales 869. When to use classed and when to use unclassed color scales 870. Patterns, predictions, and actions: A story about machine learning […]
Category: statistics
Lasso regression
Lasso står for “least absolute shrinkage and selection operator” (Tibshirani 1996). Lasso regression er en teknik inden for maskinlæring, der især anvendes når man arbejder med data med mange dimensioner. Konkret begrænser man en models fleksibilitet gennem regularisering ved hjælp af en tabsfunktion. Lasso er især anvendeligt når vi har en lang række af uafhængige […]
A few studies you should read before you do a mediation analysis
I am tired of reading and reviewing academic studies using mediation analysis, especially when researchers are relying on cross-sectional, observational data. None mentioned, none forgotten. In the best possible world, people would read more Pearl and understand the challenges of demonstrating empirical evidence in line with causal pathways (and maybe reconsider whether they want to […]
Polls and the 2020 Presidential Election
In 2016, opinion polls – and in particular poll-based prediction models – suffered a major hit with the inability to predict the election of Donald J. Trump as the president of the United States. If you want a quick reminder, take a look at this forecast from the 2016 Presidential Election: The 2020 Presidential Election […]
Potpourri: Statistics #72 (Monty Hall problem)
858. Monty Hall Simulations 859. Making the Monty Hall problem weirder but obvious 860. The Intuitive Monty Hall Problem 861. The psychology of the Monty Hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser 862. The Collider Principle in Causal Reasoning: Why the Monty Hall Dilemma Is So Hard 863. Rationality, the Bayesian […]