Author: Bob C-J
I'm a teacher, researcher, and gadfly of neuroscience. My research interests are in the neural basis of learning and memory, the history of neuroscience, computational neuroscience, bibliometrics, and the philosophy of science. I teach courses in neuroscience, statistics, research methods, learning and memory, and happiness. In my spare time I'm usually tinkering with computers, writing programs, or playing ice hockey.


Last month I (Bob) visited a local elementary school for a “Science Alliance” visit. This is a program in our community to being local scientists into the classroom. I brought the Cartoon Network simulator I have been developing (Calin-Jageman, 2017,

Joining the fractious debate over how to do science best

At the end of the month (March 2019) the American Statistical Association will publish a special issue on statistical inference “after p values”. The goal of the issue is to focus on the statistical “dos” rather than statistical “don’ts”. Across

Sizing up behavioral neuroscience – a meta-analysis of the fear-conditioning literature

Inadequate sample sizes are kryptonite to good science–they produce waste, spurious results, and inflated effect sizes.  Doing science with an inadequate sample is worse than doing nothing.  In the neurosciences, large-scale surveys of the literature show that inadequate sample sizes

Positive Controls for Psychology – My pitch for a SIPS project

Positive controls are one of the most useful tools for ensuring interpretable and fruitful research.  Strangely, though, positive controls are rarely used in psychological research.  That’s a shame, but also an opportunity–it would be an easy but substantial improvement for

The Perils of MTurk, Part 1: Fuel to the Publication Bias Fire?

It’s not going to be a popular opinion, but I think MTurk has become a danger to sound psychological science.  This breaks my heart.  MTurk has helped transform my career for the better.  Moreover, MTurk participants are amazing: they are

We’ve Been Here Before: The Replication Crisis over the Pygmalion Effect

[UPDATE: Thanks to twitter I came across this marvelous book(Jussim, 2012) that does a great job explaining the Pygmalion effect, the controversy around it, and the overall state of research on expectancy effects.  I’ve amended parts of this post based on

Sample-size planning – a short video

Here’s a short talk I gave at the 2017 Society for Neuroscience meeting on sample size planning.  The talk discusses: Why you should plan your sample sizes in advance What not to do (how some common approaches can lead you

Why effect sizes? A tutorial (especially for Neuroscientists)

The New Statistics emphasizes effect sizes, confidence intervals, meta-analysis, and Open Science.  There’s a lot of momentum to adopt this change of focus.  For example, the APA recently released new guidelines for reporting quantitative research and throughout it emphasizes reporting

The complexity of measuring a ‘simple’ behavior (novelty preference tests seem terrible)

The replication crisis isn’t just about sample size and statistical inference.  Another key issue is measurement: the process of turning observations into quantitative statements about our sample.  It’s tricky.  In many cases we’ve run before we learned to walk, adopting methods

Pre-Print – The New Statistics for Better Science

We have a new preprint on how the New Statistics can save the world (sort of):  It’s for a special issue of the American Statistician on the them of  “Beyond p values”. We welcome your feedback on via email, twitter (@TheNewStats),