Humor4u

If only post hoc analyses always brought out the inner skeptic in us all! Or came with red flashing lights instead of just a little token "caution" sentence buried somewhere.  Post hoc analysis is when researchers go looking for patterns in data. (Post hoc is Latin for "after this.") Testing for statistically significant associations is not by itself a way to sort out the true from the false. (More about that  here .) Still, many treat it as though it is - especially when they haven't been able to find a "significant" association, and turn to the bathwater to look for unexpected babies. Even when researchers know the scientific rules and limitations, funny things happen along the way to a final research report. It's the problem of  researchers' degrees of freedom : there's a lot of opportunity for picking and choosing, and changing horses mid-race. Researchers can succumb to the temptation of over-interpreting the value of what they'r

In an earnest attempt to reach more people (or perhaps a desperate attempt to build up a larger audience) I though it would be good to post this reference to the existing five (5) episodes of the podcast that Tor Norbye  and I have been working on for the past several weeks. And by "working on," I mean we get together every 2-4 weeks, sit down with someone interesting on one of the Android development teams and talk about technology and APIs that interest us, and then let someone else figure out the tedious details of actually recording and posting the results. So it's not really work as much as work- related . The goal of the podcast from the beginning was to have conversations with engineers and teams that listeners might not otherwise know and to talk about details of features and functionality of the Android platform that might not be obvious from simply reading the documentation. Because, hey, who reads the docs anyway, right? So far we've released five (5!) epi

Photo by Tzvi Meller As much as it seems counter-intuitive, teaching new vocabulary in semantic sets (e.g. jobs: doctor, teacher, lawyer etc. or colours: red, blue, yellow  etc.) does not facilitate learning. As far back as in the 1990s, research showed that teaching semantically related items is counter-productive . Have these findings been taken on board? Of course not! New vocabulary in elementary level coursebooks is routinely presented in lists of semantically related items. Semantic sets and interference In 1993, Thomas Tinkham investigated the effect of learning new words under two conditions. One group received a list of words belonging to the same semantic set while the other was given random, semantically unrelated words. Tinkham revealed that list-learning of unrelated words yielded better results as the second group performed significantly better when they were asked to recalled the target words. A few years later, Rob Waring (1997) replicated the experiment with two groups