#pvalues — Public Fediverse posts

In grad school I noticed a printed message on the wall of our research lab. It was something like "distill information from the hint of implication" (bad memory).

I innocently said to an older grad student, "Yeah, that does sound like a way to commit Type-I errors" or something equivalent.

Well, that's not what the older grad student took from the sign and I got a very cold, slightly huffy response.

#statistics #probability #pvalues #typeIerror #sample #population

How to cheat at settlers by loading the dice (2017)

https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html

#HackerNews #cheat #settlers #settlersofcatan #loadingdice #gamingstrategy #pvalues

How to cheat at settlers by loading the dice (2017)

https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html

#HackerNews #cheat #settlers #settlersofcatan #loadingdice #gamingstrategy #pvalues

How to cheat at settlers by loading the dice (2017)

https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html

#HackerNews #cheat #settlers #settlersofcatan #loadingdice #gamingstrategy #pvalues

How to cheat at settlers by loading the dice (2017)

https://izbicki.me/blog/how-to-cheat-at-settlers-of-catan-by-loading-the-dice-and-prove-it-with-p-values.html

#HackerNews #cheat #settlers #settlersofcatan #loadingdice #gamingstrategy #pvalues

@lakens Your discussion of #pvalues is really a bit odd. "Just calculate a number that has no real interpretation, and then interpret it cautiously."* That's bogus.

Importantly, you missed the opportunity to making the point that, relatively, your p-values do have an interpretation: If you order your effects by p-value from low to high, the top of this list contains better candidates for a future study than the bottom.

*these are my words paraphrasing/interpreting Daniel Lakens

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

Surveys, coincidences, statistical significance 🧵

"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna

@edutooters

#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference

Surveys, coincidences, statistical significance 🧵

"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna

@edutooters

#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference

Surveys, coincidences, statistical significance 🧵

"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna

@[email protected]

#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference

Surveys, coincidences, statistical significance 🧵

"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna

@edutooters

#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference

Surveys, coincidences, statistical significance 🧵

"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna

@edutooters

#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference

Jacob Cohen: we, as teachers, consultants, authors, and otherwise perpetrators of quantitative methods, are responsible for the ritualization of null hypothesis significance testing,,, to the point of meaninglessness and beyond.

Wendy's teenager: Um, sir...

#whycharactergotsirthisiswendys
#hashtaggames

#psychology #statistics #pvalues #rants

#statistics #pvalues #math #analytics

@level98

😀
There even wikipedia on the "Misuse of p-values": https://en.wikipedia.org/wiki/Misuse_of_p-values

I therefore am adding to my guidelines: "Instead of telling researchers what they want to know, statisticians should teach researchers which questions they can ask. […]
Before we can improve our statistical inferences, we need to improve our statistical questions."

Excerpt from Daniël Lakens (2021) https://journals.sagepub.com/doi/10.1177/1745691620958012

#quotes #nullHypothesis #probability #math #pValues #maths #AIEthics #ML #statistics

There's a #debate in #ExperimentalPhilosophy (#xPhi) about whether #intuitions about philosophical thought experiments are "stable" (vs. manipulable).

Some (e.g., @xphilosophy) seem convinced of stability—e.g., because some replications of instability results and new experiments find #pValues > 0.05.

Alexander & Weinberg express a different view (https://philpapers.org/rec/ALEPMP). I agree that the debate needs parties to agree on a smallest effect size of interest.

Page images attached.