Stats and Methods Urban Legend 4: Effect Size vs. Hypothesis Testing
Yet another article in the null hypothesis significance testing (NHST) and effect size testing (EST) debate. Perhaps we should use both?
technology, education and training from an industrial/organizational (I/O) psychologist
Yet another article in the null hypothesis significance testing (NHST) and effect size testing (EST) debate. Perhaps we should use both?
In what I can only assume is a special issue of Organizational Research Methods, several researchers discuss common statistical and methodological myths and urban legends (MUL) commonly seen in the organizational sciences (for more...
The use of control variables to purify statistical analyses is most often an invalid approach to solving the problem of poor methodology and design.
There are two models of the relationships between constructs and measures: reflective and formative. And formative’s got some issues.
Use poorly constructed figures in the news media to learn or teach statistics! Because there are certainly plenty of them.
In the first paper I’ve seen using social media (like Twitter) to tie to a real world monetary outcome, Asur and Huberman (2010) at the Social Computing Labs in Palo Alto, CA use Twitter activity to predict film box office sales. Taking all 24 major film releases between November 2009 and January 2010, the number of tweets on new films predict sales even better than the Hollywood Stock Exchange (HSX), an online prediction game (think fantasy football for film success) that is described as the “gold standard” for predicting box office revenues.