Lies, damn lies, and statistics.
So, I saw an article in the online edition of Sporting News this morning (http://www.sportingnews.com/us/mlb/news/average-mlb-salary-falls-for-only-fourth-time-in-50-years-first-time-since-200/y0pslbvbu9pf1u16kb4mubxt8) that said the average major league salary for 2018 was about 4.52 MILLION dollars. Since I'd not yet finished my first cup of coffee I stared at that number for a minute and then said "that doesn't make sense." My reasoning was this: there are somewhere over 900 MLB players (30 teams, 25 players each, plus all the players on the diabled list) and a few of them make enormous salaries - more than $20 million a year, while the minimum MLB salary is a paltry $545,000. By the way, the highest paid MLB player in 2018 is Mike Trout of the Anaheim Angels at a cool $33.25 million and the top 25 players in the league all make more than $22 million. So, $4.52 million as an indication of what the "average" MLB player makes seems way off the mark. And after some more digging I discovered I was correct. While the AVERAGE salary is $4.52 million, the MEDIAN salary is a meager $1.5 million. This is a much more accurate indicator of what MLB players actually are making. Now, nearly every article I found on my Google search reported the average salary figure and I had to dig around quite a bit to find the median. It strikes me that the stories that just reported the average salary were slanted towards the "wow MLB players make way too much money" opinion, and they emphasized the average deliberately (IMHO) because that number was so much higher than the median value.
Just goes to show you that you should always think about what you're reading in any media. (And just to say that I would have played for just one year at that average salary; just pick a position. Really. 😎).
Saturday, December 22, 2018
Monday, September 10, 2018
New Book!
Springer-Verlag has just published my latest cryptology book History of Cryptography and Cryptanalysis: Codes, Ciphers and their Algorithms. If you read it, please let me know your opinion!
https://smile.amazon.com/History-Cryptography-Cryptanalysis-Algorithms-Computing/dp/3319904426/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=1536610952&sr=8-1
https://smile.amazon.com/History-Cryptography-Cryptanalysis-Algorithms-Computing/dp/3319904426/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=1536610952&sr=8-1
Monday, July 2, 2018
Billions and Billions and Billions of numbers...
So a week or so ago, someone got access to one of my credit card numbers and started buying things at the iTunes store. Capital One was on the job and immediately sent me text messages and emails asking "Is this you?" When I said "NO!" and submitted a fraud report they immediately canceled that card and got the charges rescinded and then within about 15 minutes they got me a new credit card number and said they'd be mailing me the new card (it arrived about 3 days later). This is all very cool. It was a bit inconvenient because this particular card was the one I used for all my Internet purchases (I use a different card for non-internet stuff), but eventually I got it all straightened out.
But then I started thinking about Capital One and how many new cards - and card numbers - they must generate in a single day. I also started wondering about how many credit card numbers there were and when they'd run out of numbers (like the IPv4 internet addresses - there are only 4 billion of them and we actually ran out several years ago, hence IPv6). Clearly the credit card companies don't re-use credit card numbers. Also clearly there are a finite supply of them. So eventually we'll run out right? Well, here's the math...
All the credit cards I have and know about use 16-digits for your credit card number, plus you also have a security code of either 3 or 4 digits. The security code doesn't enter into this computation, though. So with 16 digits that is 10^16 possible credit card numbers - 10,000,000,000,000,000 possibilities. Also remember that there are about 7 billion people on the planet.
Now if all the credit card companies give out 1 million (10^6) new credit cards a day, that's 365 million a year. It will take about 3 years to get to a billion numbers (10^9), and 3000 years to get to a trillion (10^12), and 3 million years to get to a quadrillion (10^15). So I think we're good for a while.
But, a million numbers a day divided up between 7 billion people doesn't sound like very many. What if the credit card companies gave out 1 billion (10^9) new credit card numbers a day? Well, doing the same math we get 365 billion numbers per year. I will take 3 years to get to a trillion numbers (10^12) and 3000 years to get to a quadrillion (10^15) and 30,000 years to get to 10^16. So even if every person on the planet gets a new credit card every week we're still good for about 30,000 years. I'm happy.
But wait. There are other numbers. Your Social Security Number is only 9 digits long, which means there are only a maximum of 1 billion (10^9) possible numbers. There are currently about 325 million Americans with Social Security numbers, not counting all the dead people who had SSNs. So aren't we going to be running out of SSNs real soon now?
It turns out yes, and no. There's a great answer to this question on Quora that says that we've only used about 480 million of the billion possible numbers (there are actually fewer because some are excluded, like 000-00-0000 and 999-99-9999) and we're using them up at the rate of about 5.5 million a year. At that rate we'll use them all up in about 95 more years and we'll then have to either increase the length of your SSN, add a letter, or start reusing dead people's numbers. In 95 years I'd be over 150 years old, so I don't think I have to worry.
But then I started thinking about Capital One and how many new cards - and card numbers - they must generate in a single day. I also started wondering about how many credit card numbers there were and when they'd run out of numbers (like the IPv4 internet addresses - there are only 4 billion of them and we actually ran out several years ago, hence IPv6). Clearly the credit card companies don't re-use credit card numbers. Also clearly there are a finite supply of them. So eventually we'll run out right? Well, here's the math...
All the credit cards I have and know about use 16-digits for your credit card number, plus you also have a security code of either 3 or 4 digits. The security code doesn't enter into this computation, though. So with 16 digits that is 10^16 possible credit card numbers - 10,000,000,000,000,000 possibilities. Also remember that there are about 7 billion people on the planet.
Now if all the credit card companies give out 1 million (10^6) new credit cards a day, that's 365 million a year. It will take about 3 years to get to a billion numbers (10^9), and 3000 years to get to a trillion (10^12), and 3 million years to get to a quadrillion (10^15). So I think we're good for a while.
But, a million numbers a day divided up between 7 billion people doesn't sound like very many. What if the credit card companies gave out 1 billion (10^9) new credit card numbers a day? Well, doing the same math we get 365 billion numbers per year. I will take 3 years to get to a trillion numbers (10^12) and 3000 years to get to a quadrillion (10^15) and 30,000 years to get to 10^16. So even if every person on the planet gets a new credit card every week we're still good for about 30,000 years. I'm happy.
But wait. There are other numbers. Your Social Security Number is only 9 digits long, which means there are only a maximum of 1 billion (10^9) possible numbers. There are currently about 325 million Americans with Social Security numbers, not counting all the dead people who had SSNs. So aren't we going to be running out of SSNs real soon now?
It turns out yes, and no. There's a great answer to this question on Quora that says that we've only used about 480 million of the billion possible numbers (there are actually fewer because some are excluded, like 000-00-0000 and 999-99-9999) and we're using them up at the rate of about 5.5 million a year. At that rate we'll use them all up in about 95 more years and we'll then have to either increase the length of your SSN, add a letter, or start reusing dead people's numbers. In 95 years I'd be over 150 years old, so I don't think I have to worry.
Friday, June 29, 2018
Furor over diversity in CS Higher Ed
A few days ago Stuart Reges, a CS prof at the University of Washington wrote an opinion piece at Quillette.com on "Why Women Don't Code". It's started quite the furor in the CS higher education community and garnered more than 325 comments and not all of them nice or civil. I won't even talk about the stuff that's come out on Twitter. There have been some good, well reasoned and reasonable responses. Here's a good response to Reges' article from Scott Jaschik at Inside Higher Education titled Furor on Claim Women's Choices Create Gender Gap in Comp Sci
The best comment here is the first one after the article (by "Helen") that tries to be also reasonable and is also well thought out. After that first comment most of the men responding in the rest of the comments devolve into defensive drivel almost immediately...
While I think that Reges has a point about women making a choice not to pursue CS and I like his "equality" vs "equity" models, his argument is much too narrow and he doesn't consider many other contributing factors besides the intro courses and the welcoming attitude of the department that will go into those choices. But it's a good discussion to have. I also don't agree with Reges' defense of Damore (the fired and allegedly misogynistic Google engineer) since if I remember correctly, Damore's argument was that women weren't biologically capable of coding as well as men. That's just stupid and merits no defense.
These articles and the discussion they have started are worth having - as long as we can all remain civil.
Wednesday, June 13, 2018
Quitting my Ph.D. program
I've just retired from a full-time gig as a tenured professor of computer science. It was my dream job and I loved it. I taught in two different places for a total of 22 years. I also worked in the computer industry for a bit over 16 years, ending up as the VP of development for a startup software company. And I did it all without a Ph.D.
I've never really talked about the whole story of how and why I never finished my Ph.D. and I didn't really need to because I was lucky and found places that would hire me without one. But recently one of my former students has also quit her Ph.D. program and has just written an excellent essay on how that all worked for her. (her essay is here) So I thought I'd go through what I experienced when I quit my program.
In a sense, I quit two Ph.D. programs. I started grad school at Syracuse University as a Ph.D. student in mathematics (I have a B.A. in liberal arts with a major in math.) After my first semester of grad school I decided that I was not cut out to be a mathematician (that would be another long post) and I switched from mathematics to computer science. A year and a half later I got my M.S. in CS and high-tailed it out of upstate New York and went to work.
My problem was that, while I liked the software development jobs I got, what I really wanted to do was teach undergraduates. I was a math TA in grad school and really loved being in the classroom and interacting with students. Working in industry I missed that interaction. Really, my passion was teaching. After a year or so I started picking up adjunct teaching positions. I'd teach Introduction to CS, Data Structures, and the odd programming language class. That certainly helped and got me back in the classroom, but wow was I exhausted. Working full time in software development and then teaching for 3-4 hours in the evening, plus creating lectures, grading, etc. was a lot, even in your 20s.
So after a couple of years I decided to go back to grad school, finish the Ph.D. and get a teaching job at an undergraduate institution. This time I was at Rice University. At that time - 1978 or so - Rice didn't have a CS department. CS was split between the Electrical Engineering department (for the hardware bits) and Mathematical Sciences (for the theoretical bits). Since I was more interested in hardware and operating systems at that time I ended up in the EE department. Over the course of four years I finished all my coursework, passed my qualifying exams, and started research in networking algorithms (specifically using max-flow-min-cut algorithms to help design distributed operating system software). This should all have ended with me finishing the research, getting a publication or two, writing a dissertation, and then making my way into academia. Or not. As happens with many plans, life decided to interrupt. I went through a divorce. I was the first doctoral student for my Ph.D. advisor and it turned out he wasn't very good at it - and neither was I. It also didn't help that because I'd already been out in industry and in grad school once, that I was actually a year older than my adviser. I struggled with some of the mathematics we were using. And then just to make things more difficult a paper was published that proved that a similar research problem to the one we were working on was NP-complete, which kind of threw a wrench into our solutions. Finally, I frankly didn't really know how to do research at that time and I wasn't very good at it. So I got Rice to give me a second Master's degree, this time in EE, and I quit.
I packed it in and headed back to industry. For a long time I felt like a failure, even though I subsequently had a very successful career as a developer and a manager. I was convinced that I was merely a dilettante and was incapable of finishing any difficult intellectual task. This despite the fact that I was writing complex operating system software pretty much every day.
The hardest part was that I really wanted to teach and for several years I thought that was just out the window. But, I finally started feeling better about myself. I decided that while failures on my part might be the reason for leaving my Ph.D. program, that in the end it was better for my life going forward. I still had many things to learn to get to the level that I supposed I needed to be at to do research and teach. It helped that early on in this process I got married to my wonderful wife of now 32 years and we had a son. I found a way to do some publishing while I was still working in industry, and I went back to teaching as an adjunct. Then I had the incredible luck to be fired from my last job in industry. Really. In my startup job my boss (who was a psychologist, not a tech person) didn't like some of the software project management innovations I was adding to the development process, so she fired me. That company is now barely alive, but there's no shadenfreude here; well, not much. Getting fired was the best thing that happened to me.
Those things eventually gave me the confidence to apply for the teaching job of my dreams at Knox College. It also helped that at that time (2001) Knox had a terrific Dean who was willing to take a chance on a 48-year-old guy with two master's degrees to teach CS full-time in a struggling program. Sixteen years later I retired as a tenured full professor in an endowed chair and a thriving department with really terrific colleagues.
I guess my point is that just because you've decided to walk away from one thing, doesn't mean you shouldn't walk straight into something just as good, or that with a little patience you'll end up where you should be. Quitting a Ph.D. program (or anything really) isn't about failure. It's about choosing what is best for you and opening up the opportunity to try something different and be a better you. It may take a while but you can surely get there.
I've never really talked about the whole story of how and why I never finished my Ph.D. and I didn't really need to because I was lucky and found places that would hire me without one. But recently one of my former students has also quit her Ph.D. program and has just written an excellent essay on how that all worked for her. (her essay is here) So I thought I'd go through what I experienced when I quit my program.
In a sense, I quit two Ph.D. programs. I started grad school at Syracuse University as a Ph.D. student in mathematics (I have a B.A. in liberal arts with a major in math.) After my first semester of grad school I decided that I was not cut out to be a mathematician (that would be another long post) and I switched from mathematics to computer science. A year and a half later I got my M.S. in CS and high-tailed it out of upstate New York and went to work.
My problem was that, while I liked the software development jobs I got, what I really wanted to do was teach undergraduates. I was a math TA in grad school and really loved being in the classroom and interacting with students. Working in industry I missed that interaction. Really, my passion was teaching. After a year or so I started picking up adjunct teaching positions. I'd teach Introduction to CS, Data Structures, and the odd programming language class. That certainly helped and got me back in the classroom, but wow was I exhausted. Working full time in software development and then teaching for 3-4 hours in the evening, plus creating lectures, grading, etc. was a lot, even in your 20s.
So after a couple of years I decided to go back to grad school, finish the Ph.D. and get a teaching job at an undergraduate institution. This time I was at Rice University. At that time - 1978 or so - Rice didn't have a CS department. CS was split between the Electrical Engineering department (for the hardware bits) and Mathematical Sciences (for the theoretical bits). Since I was more interested in hardware and operating systems at that time I ended up in the EE department. Over the course of four years I finished all my coursework, passed my qualifying exams, and started research in networking algorithms (specifically using max-flow-min-cut algorithms to help design distributed operating system software). This should all have ended with me finishing the research, getting a publication or two, writing a dissertation, and then making my way into academia. Or not. As happens with many plans, life decided to interrupt. I went through a divorce. I was the first doctoral student for my Ph.D. advisor and it turned out he wasn't very good at it - and neither was I. It also didn't help that because I'd already been out in industry and in grad school once, that I was actually a year older than my adviser. I struggled with some of the mathematics we were using. And then just to make things more difficult a paper was published that proved that a similar research problem to the one we were working on was NP-complete, which kind of threw a wrench into our solutions. Finally, I frankly didn't really know how to do research at that time and I wasn't very good at it. So I got Rice to give me a second Master's degree, this time in EE, and I quit.
I packed it in and headed back to industry. For a long time I felt like a failure, even though I subsequently had a very successful career as a developer and a manager. I was convinced that I was merely a dilettante and was incapable of finishing any difficult intellectual task. This despite the fact that I was writing complex operating system software pretty much every day.
The hardest part was that I really wanted to teach and for several years I thought that was just out the window. But, I finally started feeling better about myself. I decided that while failures on my part might be the reason for leaving my Ph.D. program, that in the end it was better for my life going forward. I still had many things to learn to get to the level that I supposed I needed to be at to do research and teach. It helped that early on in this process I got married to my wonderful wife of now 32 years and we had a son. I found a way to do some publishing while I was still working in industry, and I went back to teaching as an adjunct. Then I had the incredible luck to be fired from my last job in industry. Really. In my startup job my boss (who was a psychologist, not a tech person) didn't like some of the software project management innovations I was adding to the development process, so she fired me. That company is now barely alive, but there's no shadenfreude here; well, not much. Getting fired was the best thing that happened to me.
Those things eventually gave me the confidence to apply for the teaching job of my dreams at Knox College. It also helped that at that time (2001) Knox had a terrific Dean who was willing to take a chance on a 48-year-old guy with two master's degrees to teach CS full-time in a struggling program. Sixteen years later I retired as a tenured full professor in an endowed chair and a thriving department with really terrific colleagues.
I guess my point is that just because you've decided to walk away from one thing, doesn't mean you shouldn't walk straight into something just as good, or that with a little patience you'll end up where you should be. Quitting a Ph.D. program (or anything really) isn't about failure. It's about choosing what is best for you and opening up the opportunity to try something different and be a better you. It may take a while but you can surely get there.
Saturday, June 9, 2018
NSA Motivational Posters
I came across a new document on the web site governmentattic.org. It's in response to a two-year old FOIA request for motivational posters that the NSA used to put up. The request was specifically for posters from the 1950s and 1960s. The request was finally granted and the NSA shipped off a pdf to governmentattic with about 135 different posters in it.
They are hysterical and very reminiscent of the attitudes that were pretty generally in place during the height of the Cold War in the 1950s and 1960s. Here are a couple of the posters:
I just love the John Travolta one! If you want to see all the posters they are at http://www.governmentattic.org/28docs/NSAsecurityPosters_1950s-60s.pdf
Enjoy!
They are hysterical and very reminiscent of the attitudes that were pretty generally in place during the height of the Cold War in the 1950s and 1960s. Here are a couple of the posters:
Enjoy!
Sunday, June 3, 2018
Hobbies and age...
Related to my previous post about hobbies, Vir Das at the Knox College Commencement today said (approximately), "You're never too old to learn a new hobby. You're just too old to do it well." I like that; it ties in well with my idea of being a dilettante as you grow older.
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