Goto

Collaborating Authors

Scary statistic of the year: 90.5% of plastic is not recycled

The Japan Times

LONDON - The world's burgeoning plastic waste crisis has won the attention of Britain's Royal Statistical Society, which chose 90.5 percent -- the proportion of plastic waste that has never been recycled -- as its international statistic of the year. The society, which chooses a winner from nominations made by the public, picked the statistic generated in a U.N. report based on the work of U.S. academics Roland Geyer, Jenna R Jambeck and Kara Lavender Law. Public awareness of the problem has been growing, particularly after filmmaker David Attenborough's documentary "Blue Planet II" showed sea turtles shrouded in plastic, among other horrors. Geyer says he was honored by the accolade and hopes "it will help draw attention to the problem of plastic pollution that impacts nearly every community and ecosystem globally."



Why You Should Care About Hypothesis Statements

#artificialintelligence

Last year, I posted an infographic titled "Hypothesis Tests in One Picture". But formulating a hypothesis statement can be tricky--and you need one to even start choosing tests. That's why I like this simplified graphic, posted on Kenyon College's website. Rather than starting with the type of data, it starts with a hypothesis statement. Do you think there's a relationship between the data?


Dax: I was molested

FOX News

Cast member Dax Shepard poses at the premiere of "This Is Where I Leave You" in Hollywood, California September 15, 2014. The movie opens in the U.S. on September 19. Dax Shepard has come forward to reveal that he was molested as a child. "It took me 12 years to tell anyone," the 41-year-old said on Sirius XM's "The Jason Ellis Show" on Monday. "And then all that time, I was like … 'It's my fault,' as generic as that is, I'm like, I'm gay, I must have manifested this because I'm secretly gay.'


diproperm: An R Package for the DiProPerm Test

arXiv.org Machine Learning

Advancements in modern technology and computer software have dramatically increased the demand and feasibility to collect high-dimensional data sets. Such data possess challenges which require the creation of new and adaptation of existing statistical methods. One such challenge is that we may observe many more predictors, p, than the number of observations, n, especially in small sample size studies. These data structures are known as high-dimensional, low sample size (HDLSS) data sets, or "small n, big p ". HDLSS data emerge frequently in many health-related fields. For example, in genomic studies, a single microarray experiment might produce tens of thousands of gene expressions compared to the few samples studied, often being less than a hundred (Alag, 2019).