havent read thru quant yet and it seems like reading chinese, is it relatively easy and how is the quickest and best way to get thru it, Q bank or cfa quesitons
qbank- skip CFAI q’s. prob will be 1 item set, just grab the low hanging fruit- learn your anova table. learn heteroskedasticity, serial corr, multicollinearity how to detect/correct. there are a ton of qbank q’s on quant. it might not get you to a 6/6, but my guess is with that alone you could pretty easily 4/6 it and spend time elsewhere if you’re hurting for time. quant is not where i’d be spending those last hours.
I hate quant too but here’s a tip that might help. I also thought it sounded like absolute gibberish even though I had been through the topic a couple of times, but I found it helpful to step back for a minute and just ask myself what exactly we’re trying to do. The entire point of the quant section is to help us derive models to make forecasts. Most of them are simple in theory - linear regression is basically just the slope intercept equation we all learned in high school, right? And multiple is about the same but just adding more than one predictive factor. A great deal of the topic revolves around the problems we encounter when trying to use historical data to make predictions. So, anytime I start feeling overwhelmed or confused I just try to remember this and it starts making more sense. I’m not sure where it is (its been a while since I’ve touched quant) but I had a notebook somewhere where I just wrote down what the main goal is of each of the different pieces of quant and it helps it from sounded a little too much like “chinese” to me 
If nothing else it helps to build some intuition about what’s going on.
if you have schweser audio cds try to listed to them several times as you drive or listen the CD while looking at the schweser book. it will take a few minutes to finish the whole section and if you repeat listen the topics are slowly becoming familar. at least that what i did today.
There are really just two big topics in Quant: regression and time series. Learn time series first, because it’s shorter and probably more intuitive (you are regressing and making forecast over time; think weather forecast or stock charts). Then the hard part is regression. Two ways: you either begin with the special case (linear regression) and then proceed to the general case (multiple regression). This is Schweser’s approach. Or, you can begin with the general case (multiple regression) and go back to the special case (linear regression). Depends on what type of person you are. If you have very few Quant background, Schweser’s approach is probably more appropriate. If you have good Quant background (e.g. if you are a math / stat major), you can try the other approach. I followed Schweser’s order in my first read (linear regression > multiple regression > time series) and I got pretty confused towards the end. (All the hard materials are cramped towards the end.) Then in my second read, I reversed the order. One drawback of the reversed order is that you may have some difficulty understanding linear trend models (which is a linear regression).
I have a hard time ponying up another $150 for the audio CDs when I’ve spent so much already… been watching ebay to see if any show up but no luck yet.