Author Archives: pmean

PMean: What to do about claims of borderline statistical significance

A comment about the phrase “trend towards efficiency” on the Statistical Consulting Section discussion board raised a lot of interesting commentary. The phrase refers to a setting where the p-value is not small enough to allow you to claim statistical significance, but still was close enough to 0.05 to be worth commenting on. Most of responses were fairly negative and stressed that we need to refuse to sign off on any report of publication using that phrase. I posted a response that differed from the others. Here’s the gist of what I said. Continue reading

Recommended: Making it easier to discover data sets

I heard about this from the UMKC Bioinformatics twitter feed. Google has a blog entry highlighting a new search feature they’ve developed, Dataset Search. It lets you find interesting data sets using standard Google search criteria. The system only works if people on the web provide reasonable documentation of their data sets. I’ve not had a chance to work with this yet, but it looks interesting. Continue reading

Recommended: JupyterLab is Ready for Users

Jupyter is an integrated development environment that uses a notebook interface. It was originally developed for Python, but is now available for a variety of other languages, including my favorite, R. I attended a talk about Jupyter from one of the main developers, and after explaining what Jupyter is, he demonstrated JupyterLab. JupyterLab is a new IDE that uses the same structure and files as Jupyter. It looks to be very simple but also very powerful. Continue reading