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Original post by LionMX
didnt supply any statistical analysis.
Well, that's a pretty big failure - you cannot claim something is better without comparing with baseline.
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But an extension of my question I guess is - he's persisting through this degree to get a job as a programmer (and he's a very good programmer I should add) but is it fair that his analysis skills are holding him back?
The difference between code monkey and engineer are exactly analytical skills.
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as optimization is so critical in games.
The first step to any optimization, of either business process, code, or anything else is the establishement of baseline metrics.
Next, different approaches for improvement are tried.
Unless dealing with very specific code that is limited to a few cycles only, any benefits will need to be measured using statistical techniques, that includes cache effects.
For any non-trivial system, let alone distributed algorithms, there will be a lot of math trying to determine which version is better. Increasingly, tools like R are used to mine hundreds of megabytes of performance logs to determine correlations, or techniques like genetic programming or similar are used to test large batches and evaluate them based on many criteria.
Yes - it's important. Probability and statistics are perhaps the most important skill to have for anything optimization related. Without them, one may write the meanest code possible, yet will not be able to conclusively reason about which is better - all code today is used as part of very large systems, and effects of single change are completely non-trivial.
This is also true for any engineering roles, where it is necessary to evaluate performance of teams, techniques, methodologies and similar. They are needed when evaluating results of unit tests, deploying new versions, or determining quality of improvements made, especially to server software.
PS. If working on something not-quite-new. If merely including a third-party library, then it's back to the "why do I need a degree for this".