Gina Kolata in the NY Times has been running a good series of articles on fraudulent academic publishing. The basic business model is an unholy alliance between academics looking to enhance their resumes, and quick-buck internet sites. Initially, I thought these sites were enticing naive academics. But many academics are apparently willing participants, suggesting that it’s easy to fool many promotion and award committees.
All but one academic in 10 who won a School of Business and Economics award had published papers in these journals. One had 10 such articles.
Should data mining newcomers have to learn programming at the same time? Here is a contrarian view, which advocates a GUI (“drag and drop”) environment. Even though the popularity of R (and recently, Python) is increasing.
I have just finished my Big Data course for 2017, and noted some concepts that I want to teach better next year. One of them is how to interpret and use the coefficient estimates from linear regression. All economists are familiar with dense tables of coefficients and standard errors, but they require experience to read, and are not at all intuitive. Here is a more intuitive and useful way to display the same information. The blue dots show the coefficient estimates, while the lines show +/- 2 standard errors on the coefficients. It’s easy to see that the first two coefficients are “statistically significant at the 5% level”, the third one is not, and so on. More important, the figure gives a clear view
of the relative importance of different variables in determining the final outcomes.
The heavy lifting for this plot is done by the function sjp.lm from the sjPlot library. The main argument linreg is the standard results of a linear regression model, which is a complex list with all kinds of information buried in it. Continue reading
Its economists used to champion big firms, but the mood has shifted
Source: Schumpeter: The University of Chicago worries about a lack of competition | The Economist
There is an emerging consensus among economists that competition in the economy has weakened significantly. That is bad news: it means that incumbent firms may not need to innovate as much, and that inequality may increase if companies can hoard profits and spend less on investment and wages.
Yes, I certainly see this in tech fields.The double consequences are scary.
Thanks to colleague Prof. Liz Lyons for suggesting this.
This is how home IoT ought to work. But overall, this service is going to figure in a lot of divorce lawsuits! Excerpts from the article: Continue reading
I’m going to list some oddball potential case study opportunities for my students here. (I’m teaching 3 courses in April, all requiring papers!).
Having a computer and a person you’ve never met pick clothes out for you, based on a style questionnaire and your social media photos, seems an odd concept. But San Francisco’s Stitch Fix and Le To…
Source: Style by subscription: Why clothing-to-your door is so popular – Silicon Valley
This is relevant to GPS students who are considering where they will fit in the data analytics/big data world.
Interview of Emily Robinson, who transitioned from a social science background to a career in data science, recently becoming a data analyst at Etsy.
Source: Emily Robinson, from Social Scientist to Data Scientist – FORWARDS