therealslimkt Posted August 2, 2019 Share Posted August 2, 2019 (edited) Choosing between measure theoretic probability and a graduate statistics class using Casella/Berger. I have some expectation of doing theory in the future, but I'm not all in. Which should I take? What are the important considerations? Edited August 3, 2019 by therealslimkt more informative title Quote Link to comment Share on other sites More sharing options...
gollin Posted August 3, 2019 Share Posted August 3, 2019 If you do measure theoretic probability you could simply read Casella and Berger afterwards and learn everything. Analysis is harder to learn on your own as many books eschew motivation in favour of a definition-theorem-proof type of exposition although analysis is fundamentally an intuitive subject (the rigour is just needed to refine your intuition initially). A class can really help you develop that intuitive feel for the subject, both through the broader insights of the professor and from your peers who you would be solving problems with. This is useful EVEN if you have a sufficiently well developed intuition for undergraduate analysis Quote Link to comment Share on other sites More sharing options...
Double Jump Posted August 4, 2019 Share Posted August 4, 2019 To be honest both classes would be useful if you decided to pursue econometric theory. I'd say both classes are at the same level of usefulness which is minimal. If you must choose a class I'd say pick one based on qualitative aspects rather than core content. Quote Link to comment Share on other sites More sharing options...
tutonic Posted August 4, 2019 Share Posted August 4, 2019 Measure theoretic probability theory will be more useful and will directly help you grasp certain concepts in first year metrics. Quote Link to comment Share on other sites More sharing options...
therealslimkt Posted August 5, 2019 Author Share Posted August 5, 2019 That makes sense, thanks everyone! Quote Link to comment Share on other sites More sharing options...
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