Yes, I did read your post. The point is whether asking math questions at all is valuable compared to the other questions you asked. I do not believe you particularly addressed that in your post or in this one. It is a proxy for what you are actually trying to measure - why not measure what you want to measure?
Your first asterisked point does not at all square with my experience. It depends on the program of study; I've certainly come across kids with no real pragmatic ability, and other programs that turned out, as much as you can in that environment, very pragmatic and skilled programmers. Certainly this is a skill set that improves over time. But let's not quibble over that; you raise a larger, valid point about interviewing recent grads vs more experienced people.
As far as that goes, I try to question them about school projects. "So, if I was to try to take that and do Y with it, what would be the consequences" type questions. Like you w/ the math questions, I do not expect any particular expertise and experience in actually solving the problem. But, I can start to see how they think about things. If they aren't thinking that clearly, throw them a bone and see what they do with it. Does it give them an 'aha' moment that then leads them to a better answer (I infer, perhaps incorrectly, that they can learn and be mentored), or do they just stonewall, not make the connection, or what have you. My suggestion is pretty simple. Measure what you want measured, not some proxy. I will point out that recent data suggests I am right. Google has admitted that all of their algorithm type questions are not good predictors of on the job performance, but questions about experience and "how would you X" are. I don't consider their data the last word on the subject (their hiring is quite narrow after all), but certainly suggestive.
I absolutely agree with asterisk 2, so I didn't address it.
> The point is whether asking math questions at all is valuable compared to the other questions you asked.
The author uses a graph search problem as an example - which is a very typical problem in IT. How do you approach such a problem? This is a valid math question that certainly adds value compared to other questions I might ask. It actually checks for multiple things: Does the candidate have a grasp of the underlying mathematical concepts. How does the candidate approach a problem decoupled of the actual real-world constraints of a programing language? Can the candidate describe a problem in clear, concise terms? Same for set theory: intersection, union, functions mapping input to output. Complexity analysis of algorithms - all of that is valuable knowledge and it's absolutely valid to ask people for that. How does binary AND/OR/XOR work? How does an exponential decay curve look like compared to a gauss or linear curve? This GH issue https://github.com/elasticsearch/elasticsearch/issues/3423 was posted on HN as example of a great feature description and it's full of formulas describing how it works. Vectors, matrix multiplication is a fundamental thing when you're doing natural language processing. Statistical problems are not exactly uncommon in programming either. Map/reduce are mathematical concept. What's wrong asking for that? Failing the answer does not mean that the interview is over, but to assert a candidate I need to know what she knows. As annoying as it sometimes is, math is _the_ _fundamental_ underpinning of what we do every day.
> As far as that goes, I try to question them about school projects.
Totally fine and I agree. Still - what's wrong with asking math questions?
> Google has admitted that all of their algorithm type questions are not good predictors of on the job performance
You're running into a problem if you hire only for math knowledge. But -repeat- that's not what I've been advocating.
Your first asterisked point does not at all square with my experience. It depends on the program of study; I've certainly come across kids with no real pragmatic ability, and other programs that turned out, as much as you can in that environment, very pragmatic and skilled programmers. Certainly this is a skill set that improves over time. But let's not quibble over that; you raise a larger, valid point about interviewing recent grads vs more experienced people.
As far as that goes, I try to question them about school projects. "So, if I was to try to take that and do Y with it, what would be the consequences" type questions. Like you w/ the math questions, I do not expect any particular expertise and experience in actually solving the problem. But, I can start to see how they think about things. If they aren't thinking that clearly, throw them a bone and see what they do with it. Does it give them an 'aha' moment that then leads them to a better answer (I infer, perhaps incorrectly, that they can learn and be mentored), or do they just stonewall, not make the connection, or what have you. My suggestion is pretty simple. Measure what you want measured, not some proxy. I will point out that recent data suggests I am right. Google has admitted that all of their algorithm type questions are not good predictors of on the job performance, but questions about experience and "how would you X" are. I don't consider their data the last word on the subject (their hiring is quite narrow after all), but certainly suggestive.
I absolutely agree with asterisk 2, so I didn't address it.