HN is a perfect example of an classic, evergreen product. Or call it a crocodile product, as crocodiles are somewhat location-loyal.
Are there more examples of products that did (on purpose) not change significantly?
If you consider the sentiment on the recent GMail redesign, Facebook, .. it often appears that product managers are the only ones that want to change the product and its appeal. I think Reddit also had the crocodile concept for long time. Google‘s main search page changed minor since the past 10 years. I guess there are more examples (Quora, Craigslist, Wikipedia..?)
@pavlov your examples capture the could-be quite well.
I really hope that the ShareLaTeX UX will survive. If I had to use Overleaf's UI, I might seriously consider canceling the subscription. The dark theme is nothing you want to use on a daily basis. Otherwise, ShareLaTeX also worked much faster and had way better example snippets, I think?
I'm optimistic that you do the transition, with Open Source.
This series might be interesting for anyone interested in a personal story of science at the intersection of research, speaking, travels, and family. Enjoy!
"A paper from the Open Science Collaboration (Research Articles, 28 August 2015,aac4716) attempting to replicate 100 published studies suggests that the reproducibility of psychological science is surprisingly low. We show that this article contains three statistical errors and provides no support for such a conclusion. Indeed, the data are consistent with the opposite conclusion, namely, that the reproducibility of psychological science is quite high."
As a non-expert, may I ask (as the term does not appear in the paper): How valuable is the Shannon number in order to evaluate "complexity" in your context?
It's just a recommendation to improve the reporting, no general defense of p-values. Pearson does not imply to analyze a causal relationship. I see the point it's not linear (then you would have had a fitted linear reg, I assume) but still can tell you that missing p-values may cause arching eyebrows :)
In small sample sizes, correlation can easily be significant, often at the cost of low confidence. To the opposite, in large sample sizes, the magnitude of the effect may be lower but at higher confidence. In both cases, results have to be interpreted with caution. The recent p-value debate points towards a lot of issues here. For instance, there have been medical studies overestimating correlations in small sample sizes while other authors seemed to underestimate their long-term large-sample results with correlations in the ballpark of 0.15 (p<0.05).
In the evaluation of correlations, it can always be informative to know the confidence interval for r, with all caution towards p-value interpretation.
Surely, correlation provides information on association rather than cause and effect (causation should rather be modeled with Granger and other regression models). Sample sizes and variances will certainly contribute to different p-value outcomes. This is because p-values reward low variance more than the magnitude of impact (Type I/II error etc.). If you have p-values, better report them and add a footnote on how to interpret them.
Knowing some MIT startups pretty well for some time, I can only partly confirm the comparison for the past. Since the school pushed some entrepreneurship activities across campus (100k, Idea Lab, Beehive, Martin Trust Center for Entrepreneurship, MediaLab) and departments, lots of things changed. It might be true that the school tries to learn from the West in terms of marketing and communications. I might agree that the talent of the East is still more on the engine while the West is better at chassis. It might also be true that the average MIT student rather enjoys being defined as a product magician solving a complex problem than a salesman wo re-invents the way how the product is packaged and communicated (both deserves its credit). However, the focus is merely on the product solution where thinking about the end-consumer often flows in a little later, sometimes too late. But as some successful examples show, the ugly duckling often bears a beautiful swan inside, once someone puts hands on user experience. Also, there are a few collaborative startups coming up in the recent two years, where founders join from different coasts and try to match the best of two worlds. At least that was my observation.
Last but not least, the YC embassadors in the Boston area and alumni (Dropbox etc.) did a great job in sharing their experiences.