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Math is just one of the ways to think about problem. But you need not have a math degree to analyze data. People do it all the time even without math. Data ana
by ordu 9y ago
Math is just one of the ways to think about problem. But you need not have a math degree to analyze data. People do it all the time even without math.
Data analysis needs understanding casualities and correlations, and ability to use some handy tools, like chi-squared. The more tools you can use, the better analyst you are.
I know some psycology scientists who have no math background at all, but who can setup an experiment and do statistical analisys on data gathered. They have a pretty good understanding on what they do while its not strictly math understanding. Math is a tool and as with any other tool you need not to understand how a tool works, you need to know how to use that tool.
In recent times you even need not know nothing about calculations behind different statistical tests, because there are computers and software that are happy to calculate anything for you.
- kenjackson 9y agoData analysis without knowing math sounds like a great way to make a bunch of analysis mistakes. I know math decently and data analysis is still hard. The whole field of causality is becoming more rigorous - see the work by Judea Pearl, for example.
- ordu 9y agoYes, of course, math is needed, when you try to do something more complex than just separate two hypothesis with a ready-made method. But to start with data analisis you need no math. It is about different levels of qualifications.
- chibg10 9y agoIsn't this the type of thinking that led to the replication crisis?
- ordu 9y agoThe repication crisis is rooted not in math but in between math and reality. Math do not work with reality, math lives in its own ideal universe. To use math for data analisis we need reason about how much data we need to separate hypothesis, we need choose acceptable p-value, we need to choose math methods. There are guides how to choose method for data, that guides needs no math but understanding what experiment is. There are 'experimental psychology', and a bunch of good books on this topic, covering all concepts that one needs to speak about choosing math methods. As for p-value and sample sizes -- there are agreement that experiment needs ~30 people and p<0.05. If we add something like ability to use R or SPSS, then we get scientist skilled enough to setup good experiment. The replication crisis is not error of individuals, it is system error. Psychology is much more complex than, for example, quantum physics, there are much more causal links in psychology and no one know even how to speak about mind, for example: is it possible to differentiate perception from memory or from thinking? Perception cannot work without memory, and there are no way to separate them as phenomena. Psychology is much more complex than psysics, and at the same time for physicist is is normal to have p<0.001 or sample size of 10k data points, while psychology is bound to p<0.05 (it is probability to get false positive) and sample size of 30. This is itself explains while physics have no replication crisis while psychology have one.
- chibg10 9y agoIn order to judge whether your math matches reality, you need to understand the math in the first place though. If you don't, then you're bound to repeatedly make mistakes.