Another School Shooting

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Originally Posted by ]-[ @ n $ 0 |v| a T ! ©

Not over. Better.

http://i227.photobucket.com/albums/d...EdenFlying.jpg

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That pic brings me tears of joy. You are lucky man... (as am I...)


Jamie

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Originally Posted by ]-[ @ n $ 0 |v| a T ! ©

It's just you. I don't even think my sister, little Suzie home-maker (who goes to church every Sunday), has even tasted beer.



Not over. Better.

http://i227.photobucket.com/albums/d...EdenFlying.jpg

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That is they way it should be....But you are not self centered....

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Originally Posted by captdg

Doc.. over my lifetime, I have known three women with children who had Autistic/Asbergers syndrome.. They had several traits in common. One they all had above average I.Q.'s Two, they got bored with any mate they had and used any excuse to move on . Three, they used babysitters excessively and liked being a popular mom down at the nightclub. One that I knew even looked like Casey Anthony.. Now.. Im NOT saying that this is the cause of of any of it, Im sure there are autisic children that have 2 loving caring well adjusted parents ..But boy they were in denial at first and wanted their kid to be in the general population at school.. Is this me being stero typical or is their any correlation? I have always believed that when one has a child...The party is OVER.

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No.

There is no correlation whatsover. You can be a great parent or a terrible parent it's not going to have ANY bearing on whether a child is born with a form of Autism.

Just curious... Do you guys (in the US) spell Aspergers differently? I noticed you and Docbennett both refer to it as 'Asbergers'. No biggie, just curious.

Hans... great pic!

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Originally Posted by DirtyMoonsRJT

Correlation does not equal causation.

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As my statistics professor taught me many many years ago...it does, when the correlation is 1.0. :biggrin: A correlation of 1.0 = "de facto causation"

You can never infer causation from correlation analysis...but, as the .r approaches 1.0 and exceeds .9....you have virtual causation, although you can never actually state that Variable A results in Effect B.

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Originally Posted by docbennett

As my statistics profession taught me many many years ago...it does, when the correlation is 1.0. :biggrin: A correlation of 1.0 = "de facto causation"

You can never infer causation from correlation analysis...but, as the .r approaches 1.0 and exceeds .9....you have virtual causation, although you can never actually state that Variable A results in Effect B.

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I spend much of my day performing distribution analytics, dynamic correlation analysis, hedging and tail risk truncation functions. Correlations are limited by a wide degree of factors the most common include the impact of outliers, the potential for spurious correlation, the confusion of exogenous and endogenous variables, and the limitations of correlation to measure relationships beyond the linear. To avoid some of the problems with simple linear regression you can attempt to use multiple regression in which lagged terms, control variables, and nonlinear terms can all be included as independent variables to better specify the relationship...however I would be extremely careful with the notion of assuming de facto causation. Assumption in my world is the mother of all ****ups.:top:

:biggrin:In addition have I mentioned how much I hate the tendancy of gaussian based functions to creep up everywhere? especially where they don't belong?:mad::D

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Originally Posted by DirtyMoonsRJT

I spend much of my day performing distribution analytics, dynamic correlation analysis, hedging and tail risk truncation functions. Correlations are limited by a wide degree of factors the most common include the impact of outliers, the potential for spurious correlation, the confusion of exogenous and endogenous variables, and the limitations of correlation to measure relationships beyond the linear. To avoid some of the problems with simple linear regression you can attempt to use multiple regression in which lagged terms, control variables, and nonlinear terms can all be included as independent variables to better specify the relationship...however I would be extremely careful with the notion of assuming de facto causation. Assumption in my world is the mother of all ****ups.:top:

:biggrin:In addition have I mentioned how much I hate the tendancy of gaussian based functions to creep up everywhere? especially where they don't belong?:mad::D

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My sentiments exactly. ;)



(I have no idea what you're talking about) :flute::biggrin:

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Originally Posted by docbennett

My sentiments exactly. ;)



(I have no idea what you're talking about) :flute::biggrin:

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That made me laugh!!!:rofl: It was a longwinded way of saying there are lies...damn lies and statistics!

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Originally Posted by docbennett

My sentiments exactly. ;)



(I have no idea what you're talking about) :flute::biggrin:

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Trying to calculate an exact value for an area under a curve, will lead to a life under a bridge...My quote from trying to understand statistics.

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Originally Posted by captdg

Trying to calculate an exact value for an area under a curve, will lead to a life under a bridge...My quote from trying to understand statistics.

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That's an easy one....calculating the area accounted for within bell-shaped curve using the formula for standard deviations above and below the mean is relatively easy...you've got T-scores and related parametric stats. It's those non-parametric statistics, or worse...any attempt to extract differentials in calculus or to do factorials that leads directly to my sitting in a squatting position under said bridge with a syringe, a dirty spoon, a PRS Zippo lighter, and a copy of Bruning and Kintz's Computational Handbook of Statistics.

brother..could you pass the Sterno, please?