Month: March 2019

Moving to a World Beyond “p < 0.05”

The 43 articles in The American Statistician discussing what researchers should do in a “post p<.05” world are now online. See here for a list of them all, with links to each article. The collection starts with an editorial: Go

Ditching Statistical Significance?!

Nature (!) has just published an editorial discussing and advocating that statistical significance should be ditched. For me, that’s the stuff of dreams, but I have lived to see it happen! I’m so happy! Here’s one para from the editorial:

Microworlds

Last month I (Bob) visited a local elementary school for a “Science Alliance” visit. This is a program in our community to being local scientists into the classroom. I brought the Cartoon Network simulator I have been developing (Calin-Jageman, 2017,

The Multiverse! Dances, and More, From Pierre in Paris

Our Open Science superego tells us that we must preregister our data analysis plan, follow that plan exactly, then emphasise just those results as most believable. Death to cherry-picking! Yay! The Multiverse But one of the advantages of open data

Joining the fractious debate over how to do science best

At the end of the month (March 2019) the American Statistical Association will publish a special issue on statistical inference “after p values”. The goal of the issue is to focus on the statistical “dos” rather than statistical “don’ts”. Across

Journal Articles Without p Values

Once we have a CI, a p value adds nothing, and is likely to mislead and to tempt the writer or readers to fall back into mere dichotomous decision making (boo!). So let’s simply use estimation and never report p

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