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FIRST QUARTER FINALS

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How many total hours do you expect to invest in preparing for final exams over the next 2~3 weeks?

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GMATT73
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FIRST QUARTER FINALS [#permalink] New post   25 Nov 2007, 15:22
Be honest...
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[#permalink] New post   25 Nov 2007, 15:35
I figure about 4 - 5 hours/course x 5 courses. I voted 20 as a base case, but could escalate to 25 - 30 ish if I freak out.

Thanks. L.
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[#permalink] New post   25 Nov 2007, 16:19
Well, we actually completed a quarter about 5 weeks ago, and we're about 2 weeks away from our next set of exams. They actually have 4 quarters here during the school year, as opposed to 3 quarters and a summer quarter that many schools have (that's what we had at UCLA when I was an undergrad).

I'll say I put in 10-20 hours of studying for exams. I don't really like to study for exams, so the system here works pretty well for me. We have an integrated system with regular prep, learning team and in-class discussion that forces everyone to prepare and keep up. I don't think you can effectively cram for exams; which is fine with me because it's not my thing.

I'll say I spent 10-20 hours preparing and things went pretty well. I'm not going to spend more than that this time around.
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[#permalink] New post   25 Nov 2007, 18:07
I've already taken two sets of files - one after the summer term at the end of August and another toward the end of October. Peli and I hare on similar schedules.

I barely studied at all in August because I was on top of the work and felt comfortable with the classes. But then kinda quit doing homework (and got hit by a car) for term 1, so had to make up for it in the end. It all worked out, though! I would guess I was at about 20 hours.
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[#permalink] New post   26 Nov 2007, 09:40
pelihu wrote:
Well, we actually completed a quarter about 5 weeks ago, and we're about 2 weeks away from our next set of exams. They actually have 4 quarters here during the school year, as opposed to 3 quarters and a summer quarter that many schools have (that's what we had at UCLA when I was an undergrad).

I'll say I put in 10-20 hours of studying for exams. I don't really like to study for exams, so the system here works pretty well for me. We have an integrated system with regular prep, learning team and in-class discussion that forces everyone to prepare and keep up. I don't think you can effectively cram for exams; which is fine with me because it's not my thing.

I'll say I spent 10-20 hours preparing and things went pretty well. I'm not going to spend more than that this time around.


Yeah, what pelihu said pretty much sums it up here at Darden.
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[#permalink] New post   26 Nov 2007, 16:18
I voted for 40~60 hours, but something about this morning's announcement (all finals are cumulative) sent a shiver up my spine. I thought economical forecasting and integrals were a thing of the past...NOT!
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[#permalink] New post   30 Nov 2007, 00:27
Anybody know how to interpret "adjusted R squared" on a regression/ANOVA summary report?
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[#permalink] New post   01 Dec 2007, 07:08
GMATT73 wrote:
Anybody know how to interpret "adjusted R squared" on a regression/ANOVA summary report?


Well, let's see what I remember from last term's stats class! Without checking my notes, here's what I recall:

In a simple linear regression, R-squared tells you how much of your data is explained by your model. A high r-squared is important if you're looking backward, trying to explain what has been happening in a certain relationship.

However, due to the way R-squared is derived, it gets synthetically higher for every additional independent variable you add to your model. The adjusted R-squared has a slightly different derivation to ensure it's not affected by those additional variables.

Again, a higher adjusted r-squared tells you to what extent your model explains your data set.
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[#permalink] New post   04 Dec 2007, 07:56
aaudetat wrote:
GMATT73 wrote:
Anybody know how to interpret "adjusted R squared" on a regression/ANOVA summary report?


Well, let's see what I remember from last term's stats class! Without checking my notes, here's what I recall:

In a simple linear regression, R-squared tells you how much of your data is explained by your model. A high r-squared is important if you're looking backward, trying to explain what has been happening in a certain relationship.

However, due to the way R-squared is derived, it gets synthetically higher for every additional independent variable you add to your model. The adjusted R-squared has a slightly different derivation to ensure it's not affected by those additional variables.

Again, a higher adjusted r-squared tells you to what extent your model explains your data set.


We also learned it is not best to always rely on R^2....

You definitely need to take a look at the Tstats, R^2 should just be a confirmation of the correlation after checking those but it is not the be all and end all.
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