Don't blame MEH for his performance Monday night

[-King-]

Originally Posted by jd1020

Because CEH was ahead of him in YPC til they were icing the Buccs game and they were just pounding the ball and Pacheco was on the field against the Raiders for all of 1 run for 0 yards.

He hasn't shown dick to say he is better than CEH and the fact he got 1 carry against the Raiders is all the evidence you need.

I mean CEH's YPC is extremely inflated by his 52 yard run. Without it he's averaging 3.4ypc. Take Pacheco's longest run out and he's still averaging 4.2.

[jd1020]

Originally Posted by -King-

I mean CEH's YPC is extremely inflated by his 52 yard run. Without it he's averaging 3.4ypc. Take Pacheco's longest run out and he's still averaging 4.2.

If only you could take out someones best run like it doesnt exist and act like sitting out an entire game in which both of them are likely to fail, preserving ones YPC, is evidence of anything.

[-King-]

Originally Posted by jd1020

If only you could take out someones best run like it doesnt exist and act like sitting out an entire game in which both of them are likely to fail, preserving ones YPC, is evidence of anything.

Why do you think both are likely to fail other than you appealing to authority?

[Megatron96]

Originally Posted by jd1020

If only you could take out someones best run like it doesnt exist and act like sitting out an entire game in which both of them are likely to fail, preserving ones YPC, is evidence of anything.

That's actually the proper way to analyze any statistical data group. Or at least it was when I took statistics in HS and college.

One of the first things you do when looking at data is to remove the largest/highest and the lowest values (they are considered outliers), then average out the rest. That eliminates most of the 'skewing' effect that one or two incongruous pieces of data can create (can't remember the proper term for that right now).

[jd1020]

Originally Posted by Megatron96

That's actually the proper way to analyze any statistical data group. Or at least it was when I took statistics in HS and college.

One of the first things you do when looking at data is to remove the largest/highest and the lowest values (they are considered outliers), then average out the rest. That eliminates most of the 'skewing' effect that one or two incongruous pieces of data can create (can't remember the proper term for that right now).

So you agree that its the proper way to go about evaluating data and then you disagree in the very next paragraph by saying you also have to remove the worst outcomes. Brilliant.

[Megatron96]

Originally Posted by jd1020

So you agree that its the proper way to go about evaluating data and then you disagree in the very next paragraph by saying you also have to remove the worst outcomes. Brilliant.

What? I think I was pretty clear. subtract the single highest and lowest values of any data set, then average the rest. One high, one low. Is that clear enough?

[jd1020]

Originally Posted by Megatron96

What? I think I was pretty clear. subtract the single highest and lowest values of any data set, then average the rest. One high, one low. Is that clear enough?

Ya, it's clear enough. I took college statistics courses. I know about outliers, idiot.

Ask yourself if the person you agreed with was doing that. I know you are brain dead so I'll help you out here... He was not.

[Coogs]

I'll bite.

What's the M in MEH stand for?

[Megatron96]

Originally Posted by jd1020

Ya, it's clear enough. I took college statistics courses. I know about outliers, idiot.

Ask yourself if the person you agreed with was doing that. I know you are brain dead so I'll help you out here... He was not.

i don't know. Did we ask him if he did? Or are you just making another assumption again?

Maybe you should just be ore concise with your language, then I wouldn't have to guess at your meaning so much.

Oh, and congrats on taking statistics. Hope you passed.