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[quote=Anonymous][quote=Anonymous]I learned how to read those tables in graduate school, in regression, causal inference (that's cause-al, not casual!) and econometrics. Those courses came AFTER I had already taken 1) undergrad stats, 2) grad stats, 3) economic modeling with calc. So that's a lot to study on your own. And I won't lie, it's difficult stuff to grasp.

Rather than go to a textbook (they will have more theory and detail than you need) I recommend you start with a study guide like "Statistics for Dummies" or "Head First Statistics" and the like. That will get you the foundation you need to move on to multivariate regression and modeling. (Those subjects will not be covered in the books named above, but you can't jump straight to them without understanding the basics, trust me.)

regression and modeling also involve calculus, but if you took algebra and pre-calc in you can probably pick up what you need. [/quote]

PP x 3 .  This person above posted while I was writing mine.  I think the comments are very helpful corroboration that you are looking at research using grad school level stats well beyond the 6 credit intro sequence.  That to me further supports a backing into understanding as you read the articles you want to read vs. getting frustrated that weeks of course time haven't addressed topics you encounter (that's how I feel about being convinced/required to take three flavors of Stats 101 and never getting to 102).

I do think everyone who reads published research should have Stats 101.  It is a reasonable bare minimum for statistical literacy.  It's like algebra.  You may not use it a lot, but you definitely should have been exposed to it.  So I commend you for looking into this and developing a plan for yourself.[/quote]

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