I'm a Psychology PhD student. As with many psychology PhD students, I know how to perform various statistical analyses using statistical software, up to techniques such as PCA, classification trees, and cluster analysis. But it's not really satisfying because though I can explain why I did an analysis and what the indicators mean, I can't explain how the technique works.
The real problem is that mastering statiscal software is easy, but it is limited. To learn new techniques in articles requires that I understand how to read mathematical equations. At present I couldn't calculate eigenvalues or K-means. Equations are like a foreign language to me.
- Is there a comprehensive guide that helps with understanding equations in journal articles?
Thanks for your comments. I thought the question would be more self explanatory: above a certain complexity, statistical notation becomes gibberish for me; let's say I would like to code my own functions in R or C++ to understand a technique but there's a barrier. I can't transform an equation into a program. And really: I don't know the situation in US doctoral schools, but in mine (France), the only courses I can follow is about some 16th century litterary movement...