Discover the Latest in Biomedical Research Innovation

Reviewers examining 100 clinical papers found 65% needed revisions just to explain what their statistical tests were for, and 64% had omitted effect sizes entirely. Statistical reporting problems are rarely about running the wrong analysis; they're about not writing down enough for a reader to judge it. Here's what belongs in the section, built on the SAMPL guidelines: seven things to state in your methods, the results formats that draw fewest queries, and a template you can

Walk into most labs and you'll find a multi-seat GraphPad Prism license that only one or two people can actually use. Prism is powerful, but its learning curve takes months, so the license sits idle while everyone waits on the lab's 'stats person.' This piece makes the case for a different GraphPad Prism alternative: Sophie, the AI you just talk to. Describe your experiment in plain English and it picks the right test, runs it, and explains the result.

Are outliers ruining your datasets? In biomedical research, distinguishing between biological variability and technical error is critical. This guide compares the traditional Grubbs’ Test against the modern ROUT method, explaining why the ROUT method's False Discovery Rate (FDR) approach is superior for detecting multiple outliers in pre-clinical data. Learn the exact protocols for GraphPad Prism and R to clean your data scientifically and avoid P-hacking.