353 karma · joined January 5, 2014
This is only mostly right. Every cell in your body has an astonishingly similar amount of DNA, but every cell division (and even steady state DNA repair) offers the opportunity for mutations. So your cells are all astonishingly similar, but there can be detectable differences.
One implication of this is that cells that are closer to each other in developmental history will have more similar DNA. One of my colleagues in graduate school used this to do phylogenetic lineaging, where he looked at markers in DNA from whole organisms to reason about which cells are closely related, and which cells have a more distant developmental ancestor.
Biology is super cool! I hope that everyone finds a little bit of it that they can enjoy. :)
Here's a nice blog post about the subject:
https://www.johndcook.com/blog/2009/01/30/server-utilization...
How do I install half of an RPM?
I don't mean to be critical. I've had a lot of advantages in life, and reading about this breaks my heart. I wish I could understand more about how I could help. None of these parents or kids deserve this situation, even if the parents could have done better.
I might be wrong though. :)
That being said, I enjoyed the algorithm for generating the next Paxos algorithm. That's fun, but I'm still not sure that I really understood what the author was saying.
https://izbicki.me/blog/how-to-create-an-unfair-coin-and-pro...
* The Elements of Statistical Learning, by Hastie, Tibshirani and Friedman (https://web.stanford.edu/~hastie/local.ftp/Springer/OLD/ESLI...). * Probability Theory: The Logic of Science, by ET Jaynes (http://bayes.wustl.edu/etj/prob/book.pdf)
Best of luck. I can see from your post that you're thinking about performance tuning, I'm assuming you mean of software. That's a nice area - the nice part is that compared to fields like medical genetics, data on performance of software is relatively cheap to get, so a lot of issues about small sample sizes are surmountable.
This method of presentation makes sense to me. Most statistics classes that I've experienced were taught from the point of view of abstract math. That's certainly one way to do it, but I knew a lot of people for whom that wasn't the optimal presentation strategy. Now that computing is cheap and there is a large audience of people with programming knowledge, I think that teaching statistics through examples of simulation, bootstrapping shuffling and cross validation is a great way to learn things.
Also, your boss might be genuinely curious. A lot of people who employ this technique precompute trajectory for arriving at their conclusion. They're often right, but the times when they're wrong are really interesting.
Bottom line - I agree with you. Don't be condescending, because you might learn something from the people around you. :)
> When the class period ended, I and the classroom teacher > believed that at least 19 of the 22 students had fully and > excitedly participated and absorbed the entire material. The > three other students' eyes were glazed over from the very > beginning, and they did not seem to be involved in the class at > all.
That's a very clear explanation that this method didn't work for every child in the class. In any class there will be children that are difficult to reach. This isn't necessarily an article about that.
I'm amazed that you think that. Why do you think that science is overcrowded, and more importantly, why is that the right thing for society? How would we know if we had too few, too many or exactly the right amount of people researching the fields you mention?