With another teaching term completed, I'm reminded of how much we faculty members rely on our Teaching Assistants (T.A.s) This is especially true in the case of large undergraduate classes, where we'd be run off our feet without the invaluable input fr...
Authors: John Mount and Nina Zumel Introduction In teaching thinking in terms of coordinatized data we find the hardest operations to teach are joins and pivot. One thing we commented on is that moving data values into columns, or into a “thin” or entity/attribute/value form (often called “un-pivoting”, “stacking”, “melting” or “gathering“) is easy to … Continue reading Teaching pivot / un-pivot
Kevin Lewis asks for my take on two new papers: Study 1: Honesty plays a key role in social and economic interactions and is crucial for societal functioning. However, breaches of honesty are pervasive and cause significant societal and economic problems that can affect entire nations. Despite its importance, remarkably little is known about the […] The post Mmore from Ppnas appeared first on Statistical Modeling, Causal Inference, and Social…
[cat picture] Russ Roberts recently interviewed me for his EconTalk podcast. We talked about social science and the garden of forking paths. Roberts was also going to talk with me about Case and Deaton, but we ran out of time. Whenever I announce a talk, people ask in comments if it will be streamed or […] The post My interview on EconTalk, and some other podcasts and videos appeared first…
Authors: John Mount and Nina Zumel. Introduction It has been our experience when teaching the data wrangling part of data science that students often have difficulty understanding the conversion to and from row-oriented and column-oriented data formats (what is commonly called pivoting and un-pivoting). Boris Artzybasheff illustration Real trust and understanding of this concept doesn’t … Continue reading Coordinatized Data: A Fluid Data Specification
Blake McShane and David Gal recently wrote two articles (“Blinding us to the obvious? The effect of statistical training on the evaluation of evidence” and “Statistical significance and the dichotomization of evidence”) on the misunderstandings of p-values that are common even among supposed experts in statistics and applied social research. The key misconception has nothing […] The post Some natural solutions to the p-value communication problem—and why they won’t work…
Ensemble methods By ensemble methods, I (Bob, not Andrew) mean approaches that scatter points in parameter space and then make moves by inteprolating or extrapolating among subsets of them. Two prominent examples are: Ter Braak’s differential evolution Goodman and Weare’s walkers There are extensions and computer implementations of these algorithms. For example, the Python […] The post Ensemble Methods are Doomed to Fail in High Dimensions appeared first on…
Last October I gave a 3-day masterclass on “Forecasting with R” in Eindhoven, Netherlands. There is a follow-up event planned for Tuesday 18 April 2017. It is particularly designed for people who attended the 3-day class, but if anyone else wants to attend they would be welcome. Please register here if you want to attend. The preliminary […]
Jason Yamada-Hanff writes: I’m a Neuroscience PhD reforming my statistics education. I am a little confused about how you treat confidence intervals in the book and was hoping you could clear things up for me. Through your blog, I found Richard Morey’s paper (and further readings) about confidence interval interpretations. If I understand correctly, the […] The post How to interpret confidence intervals? appeared first on Statistical Modeling, Causal Inference,…
Somehow I agreed or volunteered to give 6 talks on different topics to different audiences during a two-week period. Maybe I need to use Google calendar with some sort of spacing feature. Giving talks is fun, and it’s a public service, but this...
